Input: Typical generative model approaches include naive Bayes classifier s, Gaussian mixture model s, variational autoencoders and others.

naive Bayes classifier

Gaussian mixture model

variational autoencoders


Input: Finally, every other year, ELRA organizes a major conference LREC, the International Language Resources and Evaluation Conference.

ELRA

LREC

International Language Resources and Evaluation Conference


Input: The task is usually to derive the maximum likelihood estimate of the parameters of the HMM given the of output sequences.

maximum likelihood estimate

HMM


Input: Unlike neural network s and Support vector machine, the AdaBoost training process selects only those features known to improve the predictive power of the model, reducing dimensionality and potentially improving execution time as irrelevant features need not be computed.

neural network

Support vector machine

AdaBoost


Input: Troponymy is one of the possible relations between verb s in the semantic network of the WordNet database.

Troponymy

semantic network

WordNet database


Input: A frame language is a technology used for knowledge representation in artificial intelligence.

knowledge representation

artificial intelligence


Input: NIST also differs from Bilingual evaluation understudy in its calculation of the brevity penalty insofar as small variations in translation length do not impact the overall score as much.

NIST

Bilingual evaluation understudy

brevity penalty


Input: The model is initially fit on a training dataset, The model (e.g. a neural net or a naive Bayes classifier) is trained on the training dataset using a supervised learning method, for example using optimization methods such as gradient descent or stochastic gradient descent.

neural net

naive Bayes classifier

gradient descent

stochastic gradient descent

supervised learning


Input: FrameNet has been used in applications like question answering, paraphrasing, recognizing textual entailment, and information extraction, either directly or by means of Semantic Role Labeling tools.

FrameNet

question answering

paraphrasing

recognizing textual entailment

information extraction

Semantic Role Labeling


Input: This would include programs such as data analysis and extraction tools, spreadsheets (e.g. Excel), databases (e.g. Access), statistical analysis (e.g. SAS), generalized audit software (e.g. ACL, Arbutus, EAS), business intelligence (e.g. Crystal Reports and Business Objects), etc.

data analysis

statistical analysis

spreadsheets

databases

generalized audit software

business intelligence

Excel

Access

SAS

ACL

Arbutus

EAS

Crystal Reports

Business Objects


Input: Rethink Robotics - founded by Rodney Brooks, previously with iRobot - introduced Baxter in September 2012; as an industrial robot designed to safely interact with neighboring human workers, and be programmable for performing simple tasks.

Rethink Robotics

iRobot

Rodney Brooks

Baxter

industrial robot


Input: Typical text mining tasks include text categorization, text clustering, concept / entity extraction, production of granular taxonomies, sentiment analysis, document summarization, and entity relation modeling (i.e., learning relations between named entity recognition).

text mining

text categorization

text clustering

concept / entity extraction

production of granular taxonomies

sentiment analysis

document summarization

entity relation modeling

named entity recognition


Input: Nonetheless, stemming reduces precision, or TRUE negative rate, for such systems.

precision

TRUE negative rate


Input: A special case of keyword spotting is wake word (also called hot word) detection used by personal digital assistants such as Alexa or Siri to wake up when their name is spoken.

keyword spotting

wake word

hot word

Alexa

Siri


Input: Prova is an open source programming language that combines Prolog with Java.

Prova

Prolog

Java


Input: In 1987, Tocibai Machine, a subsidiary of Toshiba, was accused of illegally selling CNC milling s used to produce very quiet submarine propellers to the Soviet Union in violation of the CoCom agreement, an international embargo on certain countries to COMECON countries.

Tocibai Machine

Toshiba

CoCom

CNC milling

Soviet Union

COMECON


Input: Engelberger's most famous co-invention, the Unimate industrial robotic arm, was among the first inductees into the Robot Hall of Fame in 2003.

Engelberger

Unimate industrial robotic arm

Robot Hall of Fame


Input: Originally controlled via static html web pages using CGI, work by Dalton saw the introduction of an augmented reality Java -based interface that met with limited success.

static html

CGI

Dalton

augmented reality

Java


Input: The first publication about the LMF specification as it has been ratified by ISO (this paper became (in 2015) the 9th most cited paper within the LREC conferences from LREC papers):

LMF specification

ISO

LREC

LREC


Input: A confusion matrix or matching matrix is often used as a tool to validate the accuracy of k -NN classification.

confusion matrix

accuracy

k -NN classification


Input: Decision tree learning is one of the predictive modeling approaches used in statistics, data mining and machine learning.

Decision tree

statistics

data mining

machine learning


Input: At runtime, the target prosody of a sentence is superimposed on these minimal units by means of signal processing techniques such as linear predictive coding, PSOLA

prosody

signal processing

linear predictive coding

PSOLA


Input: This approach utilized artificial intelligence and machine learning to allow researchers to visibly compare conventional and thermal facial imagery.

artificial intelligence

machine learning

facial imagery


Input: In computer science, evolutionary computation is a family of algorithms for global optimization inspired by biological evolution, and the subfield of artificial intelligence and soft computing studying these algorithms.

computer science

artificial intelligence

soft computing

evolutionary computation

global optimization

biological evolution


Input: For instance, one can combine some measure based on the confusion matrix with the mean squared error evaluated between the raw model outputs and the actual values.

confusion matrix

mean squared error


Input: The majority are results of the word2vec model developed by Mikolov et al or variants of word2vec.

word2vec model

Mikolov


Input: It was during this time that a total of 43 publications were recognized by the CVPR and the International Conference on Computer Vision (ICCV).

CVPR

International Conference on Computer Vision

ICCV


Input: The AIBO has seen much use as an inexpensive platform for artificial intelligence education and research, because integrates a computer, Computer vision, and articulators in a package vastly cheaper than conventional research robots.

AIBO

artificial intelligence

Computer vision


Input: She served as Program Chair of International Conference on Computer Vision 2021.

International Conference on Computer Vision 2021


Input: Scheinman, after receiving a fellowship from Unimation to develop his designs, sold those designs to Unimation who further developed them with support from General Motors and later marketed it as the Programmable Universal Machine for Assembly (PUMA).

Scheinman

Unimation

Unimation

General Motors

Programmable Universal Machine for Assembly

PUMA


Input: An overview of calibration methods for binary classification and multiclass classification classification tasks is given by Gebel (2009)

binary classification

multiclass classification classification tasks

Gebel


Input: He is involved in fields such as optical character recognition (OCR), speech synthesis, speech recognition technology, and electronic keyboard instruments.

optical character recognition

OCR

speech synthesis

speech recognition


Input: For more recent and state-of-the-art techniques, Kaldi toolkit can be used.

Kaldi toolkit


Input: Johnson-Laird is a Fellow of the American Philosophical Society, a Fellow of the Royal Society, a Fellow of the British Academy, a William James Fellow of the Association for Psychological Science, and a Fellow of the Cognitive Science Society.

Johnson-Laird

William James

American Philosophical Society

Royal Society

British Academy

Association for Psychological Science

Cognitive Science Society


Input: At the IEEE International Conference on Image Processing in 2010, Rui Hu, Mark Banard, and John Collomosse extended the HOG descriptor for use in sketch based image retrieval (SBIR).

IEEE International Conference on Image Processing

Rui Hu

Mark Banard

John Collomosse

HOG descriptor

sketch based image retrieval

SBIR


Input: BLEU uses a modified form of precision to compare a candidate translation against multiple reference translations.

BLEU

precision


Input: For the case of a general base space math (Y, \ mathcal {B}, \ nu) / math (i.e. a base space which is not countable), one typically considers the relative entropy.

relative entropy


Input: As of October 2011, the already-existing partnerships with the United States' National Park Service (NPS), the United Kingdom's Historic Scotland (HS), World Monuments Fund, and Mexico's Instituto Nacional de Antropología y Historia (INAH) had been greatly expanded,, CyArk website

United States

United Kingdom

Mexico

National Park Service

NPS

Historic Scotland

HS

World Monuments Fund

Instituto Nacional de Antropología y Historia

INAH

CyArk

website


Input: Kernel SVMs are available in many machine-learning toolkits, including LIBSVM, MATLAB, and others.

Kernel SVMs

machine-learning

LIBSVM

MATLAB


Input: The 2009 Loebner Prize Competition was held September 6, 2009 at the Brighton Centre, Brighton UK in conjunction with the Interspeech 2009 conference.

Loebner Prize Competition

Brighton Centre

Brighton

UK

Interspeech 2009 conference


Input: The humanoid QRIO robot was designed as the successor to AIBO, and runs the same base R-CODE Aperios operating system.

QRIO robot

AIBO

R-CODE

Aperios operating system


Input: Speech waveforms are generated from HMMs themselves based on the maximum likelihood criterion.

Speech waveforms

HMMs

maximum likelihood


Input: Google Translate is a free multilingual statistical machine translation and neural machine translation service developed by Google, to translate text and websites from one language into another.

Google Translate

Google

multilingual statistical machine translation

neural machine translation


Input: Skeletons are widely used in computer vision, image analysis, pattern recognition and digital image processing for purposes such as optical character recognition, fingerprint recognition, visual inspection or compression.

computer vision

image analysis

pattern recognition

digital image processing

optical character recognition

fingerprint recognition

visual inspection or compression


Input: The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object classification and detection, with millions of images and hundreds of object classes.

ImageNet Large Scale Visual Recognition Challenge

object classification and detection


Input: Bengio, together with Geoffrey Hinton and Yann LeCun, are referred to by some as the Godfathers of AI and Godfathers of Deep Learning.

Bengio

Geoffrey Hinton

Yann LeCun

Godfathers of AI

Godfathers of Deep Learning


Input: He is a Life Fellow of IEEE.

IEEE


Input: NSA Bethesda is responsible for base operational support for its major tenant, the Walter Reed National Military Medical Center.

NSA Bethesda

Walter Reed National Military Medical Center


Input: The three major learning paradigms are supervised learning, unsupervised learning and reinforcement learning.

supervised learning

unsupervised learning

reinforcement learning


Input: Examples include control, planning and scheduling, the ability to answer diagnostic and consumer questions, handwriting recognition, natural language understanding, speech recognition and facial recognition.

control

planning and scheduling

answer diagnostic and consumer questions

handwriting recognition

natural language understanding

speech recognition

facial recognition


Input: In 1991 he was elected as a fellow of the Association for the Advancement of Artificial Intelligence (1990, founding fellow).

Association for the Advancement of Artificial Intelligence


Input: However, by formulating the problem as the solution of a Toeplitz matrix and using Levinson recursion, we can relatively quickly estimate a filter with the smallest mean squared error possible.

Toeplitz matrix

Levinson recursion

mean squared error


Input: In July 2011 the 15th edition of Campus Party Spain will be held at the City of Arts and Sciences in Valencia.

15th edition of Campus Party Spain

City of Arts and Sciences

Valencia


Input: Often this is generally only possible at the very end of complicated games such as chess or go, since it is not computationally feasible to look ahead as far as the completion of the game, except towards the end, and instead, positions are given finite values as estimates of the degree of belief that they will lead to a win for one player or another.

chess

go


Input: The difference between the multinomial logit model and numerous other methods, models, algorithms, etc. with the same basic setup (the perceptron algorithm, support vector machine s, linear discriminant analysis, etc.

multinomial logit model

perceptron algorithm

support vector machine

linear discriminant analysis


Input: Association for Computational Linguistics, published by

Association for Computational Linguistics


Input: In computerised Facial recognition system, each face is represented by a large number of pixel values.

Facial recognition system


Input: In 2002, his son, Daniel Pearl, a journalist working for the Wall Street Journal was kidnapped and murdered in Pakistan, leading Judea and the other members of the family and friends to create the Daniel Pearl Foundation.

Daniel Pearl

Judea

Wall Street Journal

Daniel Pearl Foundation

Pakistan


Input: As of late 2006, Red Envelope Entertainment also expanded into producing original content with filmmakers such as John Waters.

Red Envelope Entertainment

John Waters


Input: The building is now part of the Beth Israel Deaconess Medical Center.

Beth Israel Deaconess Medical Center


Input: A common theme of this work is the adoption of a sign-theoretic perspective on issues of artificial intelligence and knowledge representation.

artificial intelligence

knowledge representation


Input: For instance, the term neural machine translation (NMT) emphasizes the fact that deep learning-based approaches to machine translation directly learn sequence-to-sequence transformations, obviating the need for intermediate steps such as word alignment and language modeling that was used in statistical machine translation (SMT).

neural machine translation

NMT

machine translation

word alignment

language modeling

statistical machine translation

SMT


Input: Most research in the field of WSD is performed by using WordNet as a reference sense inventory for.

WSD

WordNet


Input: Notable former PhD students and postdoctoral researchers from his group include Richard Zemel, and Zoubin Ghahramani.

PhD

Richard Zemel

Zoubin Ghahramani


Input: Each prediction result or instance of a confusion matrix represents one point in the ROC space.

confusion matrix

ROC


Input: In 1997 Thrun and his colleagues Wolfram Burgard and Dieter Fox developed the world's first robotic tour guide in the Deutsches Museum Bonn (1997).

Thrun

Wolfram Burgard

Dieter Fox

robotic tour guide

Deutsches Museum Bonn


Input: WordNet is a lexical database of semantic relation s between word s in more than 200 languages. its primary use is in automatic natural language processing and artificial intelligence applications.

WordNet

semantic relation

natural language processing

artificial intelligence


Input: Conferences in the field of natural language processing, such as Association for Computational Linguistics, North American Chapter of the Association for Computational Linguistics, EMNLP, and HLT, are beginning to include papers on speech processing.

natural language processing

speech processing

Association for Computational Linguistics

North American Chapter of the Association for Computational Linguistics

EMNLP

HLT


Input: A set of Java programs use the lexicon to work through the variations in biomedical texts by relating words by their parts of speech, which can be helpful in web searches or searches through an electronic medical record.

Java

parts of speech

electronic medical record


Input: There are many more recent algorithms such as LPBoost, TotalBoost, BrownBoost, xgboost, MadaBoost,, and others.

LPBoost

TotalBoost

BrownBoost

xgboost

MadaBoost


Input: This is an example implementation in Python:

Python


Input: The Mattel Intellivision game console offered the Intellivoice Voice Synthesis module in 1982.

Mattel

Intellivision

Intellivoice Voice Synthesis


Input: He also worked on machine translation, both high-accuracy knowledge-based MT and machine learning for Statistical machine translation (such as generalized example-based MT).

machine translation

high-accuracy knowledge-based MT

Statistical machine translation

generalized example-based MT

machine learning


Input: Wolfram Mathematica (usually termed Mathematica) is a modern technical computing system spanning most areas of technical - including neural networks, machine learning, image processing, geometry, data science, visualizations, and others.

Wolfram Mathematica

Mathematica

neural networks

machine learning

image processing

geometry

data science

visualizations


Input: The first digitally operated and programmable robot was invented by George Devol in 1954 and was ultimately called the Unimate.

digitally operated and programmable robot

Unimate

George Devol


Input: Like DBNs, DBMs can learn complex and abstract internal representations of the input in tasks such as Object recognition or speech recognition, using limited, labeled data to fine-tune the representations built using a large set of unlabeled sensory input data.

DBNs

DBMs

Object recognition

speech recognition


Input: Scientific conferences where vision based activity recognition work often appears are ICCV and CVPR.

vision based activity recognition

ICCV

CVPR


Input: In statistics, an expectation-maximization (EM) algorithm is an iterative method to find maximum likelihood or maximum a posteriori (MAP) estimates of parameter s in statistical model s, where the model depends on unobserved latent variable s.

statistics

expectation-maximization

EM

maximum likelihood

maximum a posteriori

MAP

latent variable


Input: Similarly, investigators sometimes report the FALSE Positive Rate (FPR) as well as the FALSE Negative Rate (FNR).

FALSE Positive Rate

FPR

FALSE Negative Rate

FNR


Input: The concept is similar to the signal to noise ratio used in the sciences and confusion matrix used in artificial intelligence.

signal to noise ratio

confusion matrix

sciences

artificial intelligence


Input: The Code of Ethics on Human Augmentation, which was originally introduced by Steve Mann in 2004 and refined with Ray Kurzweil and Marvin Minsky in 2013, was ultimately ratified at the Virtual Reality Toronto conference on June 25, 2017.

Human Augmentation

Steve Mann

Ray Kurzweil

Marvin Minsky

Virtual Reality Toronto conference


Input: In 1913, Walter R. Booth directed 10 films for the U.K. Kinoplastikon, presumably in collaboration with Cecil Hepworth.

Walter R. Booth

Cecil Hepworth

U.K. Kinoplastikon


Input: They introduced their new robot in 1961 at a trade show at Chicago's Cow Palace.

Chicago

Cow Palace


Input: While some chatbot applications use extensive word-classification processes, natural language processing processors, and sophisticated Artificial intelligence, others simply scan for general keywords and generate responses using common phrases obtained from an associated library or database.

chatbot

word-classification

natural language processing

Artificial intelligence


Input: The WaveNet model proposed in 2016 achieves great performance on speech quality.

WaveNet


Input: Organizations known to use ALE for Emergency management, disaster relief, ordinary communication or extraordinary situation response: American Red Cross, FEMA, Disaster Medical Assistance Team s, NATO, Federal Bureau of Investigation, United Nations, AT & T, Civil Air Patrol, (ARES).

ALE

Emergency management

disaster relief

ordinary communication

extraordinary situation response

American Red Cross

FEMA

Disaster Medical Assistance Team

NATO

Federal Bureau of Investigation

United Nations

AT & T

Civil Air Patrol

ARES


Input: Here, the Kronecker delta is used for simplicity (cf. the derivative of a sigmoid function, being expressed via the function itself).

Kronecker delta

sigmoid function


Input: The theory is based in philosophical foundations, and was founded by Ray Solomonoff around 1960. Samuel Rathmanner and Marcus Hutter.

Ray Solomonoff

Samuel Rathmanner

Marcus Hutter


Input: WordNet, a freely available database originally designed as a semantic network based on psycholinguistic principles, was expanded by addition of definitions and is now also viewed as a dictionary.

WordNet

semantic network

psycholinguistic principles


Input: Advances in the field of computational imaging research is presented in several venues including publications of SIGGRAPH and the.

computational imaging

SIGGRAPH


Input: Classification can be thought of as two separate problems - binary classification and multiclass classification.

Classification

binary classification

multiclass classification


Input: Advanced gene finders for both prokaryotic and eukaryotic genomes typically use complex probabilistic model s, such as hidden Markov model s (HMMs) to combine information from a variety of different signal and content measurements.

probabilistic model

hidden Markov model

HMMs


Input: Neuroevolution, or neuro-evolution, is a form of artificial intelligence that uses evolutionary algorithm s to generate artificial neural network s (ANN), parameters, topology and rules. and evolutionary robotics.

Neuroevolution

neuro-evolution

artificial intelligence

evolutionary algorithm

artificial neural network

ANN

evolutionary robotics


Input: Since IBM proposed and realized the system of BLEU Papineni et al.

IBM

BLEU

Papineni


Input: In 2009, experts attended a conference hosted by the Association for the Advancement of Artificial Intelligence (AAAI) to discuss whether computers and robots might be able to acquire any autonomy, and how much these abilities might pose a threat or hazard.

Association for the Advancement of Artificial Intelligence

AAAI


Input: After boosting, a classifier constructed from 200 features could yield a 95% detection rate under a ^ {-5} / math FALSE positive rate .P. Viola, M. Jones, Robust Real-time Object Detection, 2001.

FALSE positive rate

.P. Viola

M. Jones

Robust Real-time Object Detection


Input: The website was originally Perl -based, but IMDb no longer discloses what software it uses for reasons of security.

Perl

IMDb


Input: The start-up was founded by Demis Hassabis, Shane Legg and Mustafa Suleyman in 2010.

Demis Hassabis

Shane Legg

Mustafa Suleyman


Input: Two very commonly used loss functions are the mean squared error, mathL (a) = a ^ 2 / math, and the absolute loss, mathL (a) = | a | / math.

loss functions

mean squared error

absolute loss


Input: The soft-margin support vector machine described above is an example of an empirical risk minimization (ERM) for the hinge loss.

support vector machine

empirical risk minimization

ERM

hinge loss


Input: A deep learning based approach to MT, neural machine translation has made rapid progress in recent years, and Google has announced its translation services are now using this technology in preference to its previous statistical methods.

deep learning

MT

neural machine translation

Google


Input: This tends to yield very large performance gains when working with large corpora such as WordNet.

WordNet


Input: Face detection is used in biometrics, often as a part of (or together with) a facial recognition system.

Face detection

biometrics

facial recognition system


Input: trained by maximum likelihood estimation.

maximum likelihood estimation


Input: , Ltd. in Thailand; Komatsu (Shanghai) Ltd. in 1996 in Shanghai, China; Industrial Power Alliance Ltd. in Japan, a joint venture with Cummins, in 1998; L & T-Komatsu Limited in India in 1998 (shares sold in 2013); and Komatsu Brasil International Ltda. in Brazil in 1998.

Thailand

China

Japan

India

Brazil

Komatsu (Shanghai) Ltd.

Industrial Power Alliance Ltd.

Cummins

L & T-Komatsu Limited

Komatsu Brasil International Ltda.

Shanghai


Input: dgp also occasionally hosts artists in residence (e.g., Oscar -winner Chris Landreth.

dgp

artists in residence

Oscar

Chris Landreth


Input: It currently includes four sub-competitions - the RoboMaster Robotics Competition, the RoboMaster Technical Challenge, the ICRA RoboMaster AI Challenge, and the new RoboMaster Youth Tournament.

RoboMaster Robotics Competition

RoboMaster Technical Challenge

ICRA RoboMaster AI Challenge

RoboMaster Youth Tournament


Input: By the early 2000s, the dominant speech processing strategy started to shift away from Hidden Markov model towards more modern neural networks and deep learning.

speech processing

deep learning

Hidden Markov model

neural networks


Input: Another equivalent expression, in the case of a binary target rate, is that the TRUE positive rate and the FALSE positive rate are equal (and therefore the FALSE negative rate and the TRUE negative rate are equal) for every value of the sensitive characteristics:

binary target rate

TRUE positive rate

FALSE positive rate

FALSE negative rate

TRUE negative rate


Input: The MATLAB function,

MATLAB


Input: An articulated robot is a robot with rotary joint s (e.g. a legged robot or an industrial robot).

articulated robot

industrial robot

rotary joint


Input: Pandora (also known as Pandora Media or Pandora Radio) is an American music streaming and automated Recommender system internet radio service powered by the Music Genome Project and headquartered in Oakland, California.

Pandora

Pandora Media

Pandora Radio

automated Recommender system

American

Music Genome Project

Oakland

California


Input: She is a board member of the International Machine Learning Society, has been a member of AAAI Executive council, was PC co-chair of ICML 2011, and has served as senior PC member for conferences including AAAI, ICML, IJCAI, ISWC, KDD, SIGMOD, UAI, VLDB, WSDM and WWW.

International Machine Learning Society

AAAI Executive council

ICML 2011

AAAI

ICML

IJCAI

ISWC

KDD

SIGMOD

UAI

VLDB

WSDM

WWW


Input: James S. Albus of the National Institute of Standards and Technology (NIST) developed the Robocrane, where the platform hangs from six cables instead of being supported by six jacks.

James S. Albus

National Institute of Standards and Technology

NIST

Robocrane


Input: Another class of direct search algorithms are the various evolutionary algorithm s, e.g. genetic algorithm s.

direct search algorithms

evolutionary algorithm

genetic algorithm


Input: KUKA is a German manufacturer of industrial robot s and solution s for factory automation.

KUKA

German

industrial robot


Input: Other films between 2016 to 2020 that captured with IMAX camera's were Zack Snyder' s Batman v Superman: Dawn of Justice, Clint Eastwood' s Sully, Damien Chazelle' s First Man, Patty Jenkins' Wonder Woman 1984, Cary Joji Fukunaga' s No Time to Die and Joseph Kosinski' s Top Gun: Maverick.

IMAX

Batman v Superman: Dawn of Justice

Sully

First Man

Wonder Woman 1984

No Time to Die

Top Gun: Maverick

Zack Snyder

Clint Eastwood

Damien Chazelle

Patty Jenkins

Cary Joji Fukunaga

Joseph Kosinski


Input: The trial of MICR E13B font was shown to the American Bankers Association (ABA) in July 1956, which adopted it in 1958 as the MICR standard for negotiable document s in the United States.

MICR E13B

MICR

American Bankers Association

ABA

United States


Input: Local search algorithms are widely applied to numerous hard computational problems, including problems from computer science (particularly artificial intelligence), mathematics, operations research, engineering, and bioinformatics.

Local search algorithms

computer science

artificial intelligence

mathematics

operations research

engineering

bioinformatics


Input: Gerd Gigerenzer (born September 3, 1947, Wallersdorf, Germany) is a Germany psychologist who has studied the use of bounded rationality and heuristic s in decision making.

Gerd Gigerenzer

Wallersdorf

Germany

Germany

bounded rationality

heuristic

decision making


Input: to minimize the Mean squared error.

Mean squared error


Input: But even an official language with a regulating academy, such as Standard French with the Académie française, is classified as a natural language (for example, in the field of natural language processing), as its prescriptive points do not make it either constructed enough to be classified as a constructed language or controlled enough to be classified as a controlled natural language.

Standard French

constructed language

controlled natural language

Académie française

natural language processing


Input: There are a number of other metrics, most simply the accuracy or Fraction Correct (FC), which measures the fraction of all instances that are correctly categorized; the complement is the Fraction Incorrect (FiC).

accuracy

Fraction Correct

FC

Fraction Incorrect

FiC


Input: Cardie became a Fellow of the Association for Computational Linguistics in 2016.

Cardie

Association for Computational Linguistics


Input: Learning the parameters math \ theta / math is usually done by maximum likelihood learning for mathp (Y _ i | X _ i; \ theta) / math.

maximum likelihood learning


Input: Cluster analysis, and Non-negative matrix factorization for descriptive mining.

Cluster analysis

descriptive mining

Non-negative matrix factorization


Input: In computer science and the information technology that it enables, it has been a long-term challenge to the ability in computers to do natural language processing and machine learning.

computer science

information technology

natural language processing

machine learning


Input: (Code for Gabor feature extraction from images in MATLAB can be found at

Gabor feature extraction

MATLAB


Input: The NeuralExpert centers the design specifications around the type of problem the user would like the neural network to solve (Classification, Prediction, Function approximation or Cluster analysis).

NeuralExpert

neural network

Classification

Prediction

Function approximation

Cluster analysis


Input: When the quantization step size (Δ) is small relative to the variation in the signal being quantized, it is relatively simple to show that the mean squared error produced by such a rounding operation will be approximately math \ Delta ^ 2 / 12 / math.math

quantization step size

mean squared error


Input: The construction of a rich lexicon with a suitable ontology requires significant effort, e.g., Wordnet lexicon required many person-years of effort. G. A. Miller, R. Beckwith, C. D. Fellbaum, D. Gross, K. Miller.

Wordnet

G. A. Miller

R. Beckwith

C. D. Fellbaum

D. Gross

K. Miller


Input: Kawasaki's portfolio also includes retractable roofs, floors and other giant structures, the Sapporo Dome' retractable surface is one example.

Kawasaki

Sapporo Dome


Input: Kappa statistics such as Fleiss' kappa and Cohen's kappa are methods for calculating inter-rater reliability based on different assumptions about the marginal or prior distributions, and are increasingly used as chance corrected alternatives to accuracy in other contexts.

Kappa statistics

Fleiss' kappa

Cohen's kappa

inter-rater reliability

accuracy


Input: With his students Sepp Hochreiter, Felix Gers, Fred Cummins, Alex Graves, and others, Schmidhuber published increasingly sophisticated versions of a type of recurrent neural network called the long short-term memory (LSTM).

Sepp Hochreiter

Felix Gers

Fred Cummins

Alex Graves

Schmidhuber

recurrent neural network

long short-term memory

LSTM


Input: 2004 - The first Cobot KUKA LBR 3 is released.

Cobot KUKA LBR 3


Input: Two shallow approaches used to train and then disambiguate are Naive Bayes classifier and decision trees.

Naive Bayes classifier

decision trees


Input: The first practical forms of photography were introduced in January 1839 by Louis Daguerre and Henry Fox Talbot.

photography

Louis Daguerre

Henry Fox Talbot


Input: For example, speech synthesis, combined with speech recognition, allows for interaction with mobile devices via language processing interfaces.

speech synthesis

speech recognition

language processing


Input: Phidgets can be programmed using a variety of software and programming languages, ranging from Java to Microsoft Excel.

Phidgets

Microsoft Excel

Java


Input: The term machine learning was coined in 1959 by Arthur Samuel, an American IBMer and pioneer in the field of computer gaming and artificial intelligence.

machine learning

computer gaming

artificial intelligence

Arthur Samuel

American IBMer


Input: The Israeli poet David Avidan, who was fascinated with future technologies and their relation to art, desired to explore the use of computers for writing literature.

Israeli

David Avidan


Input: As part of the GATEway Project in 2017, Oxbotica trialled seven autonomous shuttle buses in Greenwich, navigating a two-mile riverside path near London's The O2 Arena on a route also used by pedestrians and cyclists.

GATEway Project

Oxbotica

Greenwich

London

The O2 Arena


Input: An unrelated but commonly used combination of basic statistics from information retrieval is the F-score, being a (possibly weighted) harmonic mean of recall and precision where recall = sensitivity = TRUE positive rate, but specificity and precision are totally different measures.

information retrieval

F-score

recall

precision

recall

sensitivity

TRUE positive rate

specificity

precision

harmonic mean


Input: Neuromorphic engineering is an interdisciplinary subject that takes inspiration from biology, physics, mathematics, computer science, and electronic engineering to design artificial neural systems, such as vision systems, head-eye systems, auditory processors, and autonomous robots, whose physical architecture and design principles are based on those of biological nervous systems.

Neuromorphic engineering

biology

physics

mathematics

computer science

electronic engineering

vision systems

head-eye systems

auditory processors

autonomous robots

biological nervous systems


Input: To be specific, the BIBO stability criterion requires that the ROC of the system includes the unit circle.

BIBO stability criterion

ROC


Input: 2 The program was rewritten in Java beginning in 1998.

Java


Input: The MCC can be calculated directly from the confusion matrix using the formula:

MCC

confusion matrix


Input: It was developed by a team at the MIT-IBM Watson AI Lab and first presented at the 2018 International Conference on Learning Representations.

MIT-IBM Watson AI Lab

2018 International Conference on Learning Representations


Input: When the TRUE prevalence s for the two positive variables are equal as assumed in Fleiss kappa and F-score, that is the number of positive predictions matches the number of positive classes in the dichotomous (two class) case, the different kappa and correlation measure collapse to identity with Youden's J, and recall, precision and F-score are similarly identical with accuracy.

TRUE prevalence

Fleiss kappa

F-score

kappa

correlation

recall

precision

F-score

accuracy

Youden's J


Input: The Building Educational Applications workshop (BEA) at NAACL 2013 hosted the inaugural NLI shared task. Tetreault et al, 2013 The competition resulted in 29 entries from teams across the globe, 24 of which also published a paper describing their systems and approaches.

Building Educational Applications workshop

BEA

NAACL

NLI shared task.

Tetreault


Input: The Viterbi algorithm is a dynamic programming algorithm for finding the most likely sequence of hidden states called the Viterbi path that results in a sequence of observed events, especially in the context of Markov information source s and hidden Markov model s (HMM).

Viterbi algorithm

dynamic programming algorithm

hidden Markov model

HMM

hidden states

Viterbi path

Markov information source


Input: In statistics, multinomial logistic regression is a classification method that generalizes logistic regression to multiclass classification, i.e. with more than two possible discrete outcomes.

statistics

multinomial logistic regression

logistic regression

classification method

multiclass classification


Input: Hidden Markov models are known for their applications to reinforcement learning and temporal pattern recognition such as speech, handwriting recognition, gesture recognition, Thad Starner, Alex Pentland.

Hidden Markov models

reinforcement learning

temporal pattern recognition

speech

handwriting recognition

gesture recognition

Thad Starner

Alex Pentland


Input: Essentially, this means that if the n-gram has been seen more than k times in training, the conditional probability of a word given its history is proportional to the maximum likelihood estimate of that n -gram.

n-gram

n -gram

maximum likelihood estimate


Input: He is interested in knowledge representation, commonsense reasoning, and natural language understanding, believing that deep language understanding can only currently be achieved by significant hand-engineering of semantically-rich formalisms coupled with statistical preferences.

knowledge representation

commonsense reasoning

natural language understanding

deep language understanding

hand-engineering


Input: In JavaScript, Python or

JavaScript

Python


Input: The Newcomb Awards are announced in the AI Magazine published by AAAI.

Newcomb Awards

AI Magazine

AAAI


Input: The Mean squared error on a test set of 100 exemplars is 0.084, smaller than the unnormalized error.

Mean squared error


Input: The F-score has been widely used in the natural language processing literature, such as the evaluation of named entity recognition (NER) and word segmentation.

F-score

natural language processing

named entity recognition

NER

word segmentation


Input: Chatbots are typically used in dialog systems for various purposes including customer service, request routing, or for information gathering.

Chatbots

dialog systems

request routing

information gathering


Input: Important journals include the IEEE Transactions on Speech and Audio Processing (later renamed IEEE Transactions on Audio, Speech and Language Processing and since Sept 2014 renamed IEEE / ACM Transactions on Audio, Speech and Language Processing - after merging with an ACM publication), Computer Speech and Language, and Speech Communication.

IEEE Transactions on Speech and Audio Processing

IEEE Transactions on Audio, Speech and Language Processing

IEEE / ACM Transactions on Audio, Speech and Language Processing

ACM

Computer Speech and Language

Speech Communication


Input: EM is frequently used for data clustering in machine learning and computer vision.

EM

data clustering

machine learning

computer vision


Input: While there is no perfect way of describing the confusion matrix of TRUE and FALSE positives and negatives by a single number, the Matthews correlation coefficient is generally regarded as being one of the best such measures.

confusion matrix

Matthews correlation coefficient


Input: As data set s have grown in size and complexity, direct hands-on data analysis has been augmented with indirect, automated data processing, aided by other discoveries in computer science, specially in the field of machine learning, such as neural networks, cluster analysis, genetic algorithms (1950s), decision tree learning and decision rules (1960s), and support vector machines (1990s).

data analysis

computer science

machine learning

neural networks

genetic algorithms

decision tree learning

decision rules

support vector machines

cluster analysis


Input: In the fall of 2005, Thrun published a textbook entitled Probabilistic Robotics together with his long-term co-workers Dieter Fox and Wolfram Burgard.

Thrun

Dieter Fox

Wolfram Burgard

Probabilistic Robotics


Input: John D. Lafferty, Andrew McCallum and Pereiramath as follows:

John D. Lafferty

Andrew McCallum

Pereiramath


Input: Question answering (QA) is a computer science discipline within the fields of information retrieval and natural language processing (NLP), which is concerned with building systems that automatically answer questions posed by humans in a natural language.

Question answering

QA

computer science

information retrieval

natural language processing

NLP


Input: However, in the version of the metric used by NIST evaluations prior to 2009, the shortest reference sentence had been used instead.

NIST


Input: On August 27, 2018, Toyota announced an investment of $500 Million in Uber' s autonomous car s.

Toyota

Uber

autonomous car


Input: The sample maximum is the maximum likelihood estimator for the population maximum, but, as discussed above, it is biased.

maximum likelihood estimator


Input: LSI helps overcome synonymy by increasing recall, one of the most problematic constraints of Boolean keyword queries and vector space models.

LSI

synonymy

recall

Boolean keyword queries

vector space models


Input: Data acquisition applications are usually controlled by software programs developed using various general purpose programming languages such as Assembly, BASIC, C, C + +, C #, Fortran, Java, LabVIEW, Lisp, Pascal, etc.

Data acquisition

Assembly

BASIC

C

C + +

C #

Fortran

Java

LabVIEW

Lisp

Pascal


Input: In 2003, Honda released its Cog advertisement in the UK and on the Internet.

Honda

Cog

UK


Input: The Association for Computational Linguistics defines computational linguistics as:

Association for Computational Linguistics

computational linguistics


Input: Expectation-maximization algorithm s may be employed to calculate approximate maximum likelihood estimates of unknown state-space parameters within minimum-variance filters and smoothers.

Expectation-maximization algorithm

maximum likelihood estimates


Input: Correspondents included former Baywatch actresses Donna D'Errico, Carmen Electra, and Traci Bingham, former Playboy Playmate Heidi Mark, comedian Arj Barker and identical twins Randy and Jason Sklar.

Baywatch

Playboy Playmate

Donna D'Errico

Carmen Electra

Traci Bingham

Heidi Mark

Arj Barker

Randy

Jason Sklar


Input: It is commonly used to generate representations for speech recognition (ASR), e.g. the CMU Sphinx system, and speech synthesis (TTS), e.g. the Festival system.

speech recognition

ASR

speech synthesis

TTS

CMU Sphinx system

Festival system


Input: Sensitivity or TRUE Positive Rate (TPR), also known as recall, is the proportion of people that tested positive and are positive (TRUE Positive, TP) of all the people that actually are positive (Condition Positive, CP = TP + FN).

Sensitivity

TRUE Positive Rate

TPR

recall

TRUE Positive

TP

Condition Positive

CP

TP + FN


Input: Popular speech recognition conferences held each year or two include SpeechTEK and SpeechTEK Europe, ICASSP, Interspeech / Eurospeech, and the IEEE ASRU.

speech recognition

SpeechTEK

SpeechTEK Europe

ICASSP

Interspeech

Eurospeech

IEEE ASRU


Input: Devol collaborated with Engelberger, who served as president of the company, to engineer and produce an industrial robot under the brand name Unimate.

Devol

Engelberger

industrial robot

Unimate


Input: A Hidden Markov model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process with unobserved (hidden) states.

Hidden Markov model

HMM

statistical Markov model

Markov process


Input: This property, undesirable in many applications, has led researchers to use alternatives such as the mean absolute error, or those based on the median.

mean absolute error

median


Input: Such a sequence (which depends on the outcome of the investigation of previous attributes at each stage) is called a decision tree and applied in the area of machine learning known as decision tree learning.

decision tree

decision tree learning

machine learning


Input: As in factor analysis, the LCA can also be used to classify case according to their maximum likelihood class membership.

factor analysis

LCA

maximum likelihood


Input: Supervised neural networks that use a mean squared error (MSE) cost function can use formal statistical methods to determine the confidence of the trained model.

Supervised neural networks

mean squared error

MSE

cost function


Input: This can be directly expressed as a linear program, but it is also equivalent to Tikhonov regularization with the hinge loss function, mathV (f (x), y) = \ max (0, 1 - yf (x)) / math:

Tikhonov regularization

hinge loss function


Input: The following technique was described in Breiman's original paper and is implemented in the R package randomForest.

Breiman

R package randomForest


Input: Traditional image quality measures, such as PSNR, are typically performed on fixed resolution images and do not take into account some aspects of the human visual system, like the change in spatial resolution across the retina.

PSNR

retina


Input: John Ireland, Joanne Dru and Macdonald Carey starred in the Jack Broder color production Hannah Lee, which premiered June 19, 1953.

John Ireland

Joanne Dru

Macdonald Carey

Jack Broder

Hannah Lee


Input: That process is called image registration, and uses different methods of computer vision, mostly related to tracking.

image registration

tracking

computer vision


Input: Now let us start explaining the different possible relations between predicted and actual outcome: Confusion matrix

Confusion matrix


Input: The VOICEBOX speech processing toolbox for MATLAB implements the conversion and its inverse as:

VOICEBOX

MATLAB

speech processing toolbox


Input: Prolog is a logic programming language associated with artificial intelligence and computational linguistics.

Prolog

artificial intelligence

computational linguistics


Input: Milner has received numerous awards for her contributions to neuroscience and psychology including memberships in the Royal Society of London, the Royal Society of Canada and the National Academy of Sciences.

Milner

neuroscience

psychology

Royal Society of London

Royal Society of Canada

National Academy of Sciences


Input: By combining these operators one can obtain algorithms for many image processing tasks, such as feature extraction, image segmentation, image sharpening, image filtering, and classification.

image processing

feature extraction

image segmentation

image sharpening

image filtering

classification


Input: As of 2017, he is a professor at the Collège de France and, since 1989, the director of INSERM Unit 562, Cognitive Neuroimaging.

Collège de France

INSERM Unit 562

Cognitive Neuroimaging


Input: There are many approaches to learning these embeddings, notably using Bayesian clustering frameworks or energy-based frameworks, and more recently, TransE (Conference on Neural Information Processing Systems 2013).

Bayesian clustering frameworks

energy-based frameworks

TransE

Conference on Neural Information Processing Systems 2013


Input: It is an alternative to the Word error rate (Word Error Rate) used in several countries.

Word error rate

Word Error Rate


Input: ANNs have been used on a variety of tasks, including computer vision, speech recognition, machine translation, social network filtering, playing board and video games, medical diagnosis, and even in activities that have traditionally been considered as reserved to humans, like painting.

ANNs

computer vision

speech recognition

machine translation

social network filtering

playing board and video games

medical diagnosis

painting


Input: Modular Audio Recognition Framework (MARF) is an open-source research platform and a collection of voice, sound, speech, text and natural language processing (NLP) algorithm s written in Java and arranged into a modular and extensible framework that attempts to facilitate addition of new algorithm s.

Modular Audio Recognition Framework

MARF

natural language processing

NLP

Java


Input: In 2018, a report by the civil liberties and rights campaigning organisation Big Brother Watch revealed that two United Kingdom police forces, South Wales Police and the Metropolitan Police, were using live facial recognition at public events and in public spaces, in September 2019, South Wales Police use of facial recognition was ruled lawful.

Big Brother Watch

South Wales Police

Metropolitan Police

South Wales Police

United Kingdom

facial recognition

facial recognition


Input: ANIMAL has been ported to R, a freely available language and environment for statistical computing and graphics.

ANIMAL

R

statistical computing

graphics


Input: Time-inhomogeneous hidden Bernoulli model (TI-HBM) is an alternative to hidden Markov model (HMM) for automatic speech recognition.

Time-inhomogeneous hidden Bernoulli model

TI-HBM

hidden Markov model

HMM

automatic speech recognition


Input: In July 2016, Nvidia demonstrated during SIGGRAPH a new method of foveated rendering claimed to be invisible to users.

Nvidia

SIGGRAPH


Input: Both rely on speech act theory developed by John Searle in the 1960s and enhanced by Terry Winograd and Flores in the 1970s.

speech act theory

John Searle

Terry Winograd

Flores


Input: Neural network models of concept formation and the structure of knowledge have opened powerful hierarchical models of knowledge organization such as George Miller' s Wordnet.

Neural network models

George Miller

Wordnet


Input: Template matching has various applications and is used in such fields as face recognition (see facial recognition system) and medical image processing.

Template matching

face recognition

medical image processing

facial recognition system


Input: However, usage only became widespread in 2005 when Navneet Dalal and Bill Triggs, researchers for the French National Institute for Research in Computer Science and Automation (INRIA), presented their supplementary work on HOG descriptors at the Conference on Computer Vision and Pattern Recognition (CVPR).

Navneet Dalal

Bill Triggs

French National Institute for Research in Computer Science and Automation

INRIA

HOG descriptors

Conference on Computer Vision and Pattern Recognition

CVPR


Input: Prior to joining the Penn faculty in 2002, he spent a decade (1991-2001) in AT & T Labs and Bell Labs, including as head of the AI department with colleagues including Michael L. Littman, David A. McAllester, and Richard S. Sutton; Secure Systems Research department; and Machine Learning department with members such as Michael Collins and the leader).

Penn

AT & T Labs

Bell Labs

Secure Systems Research department

AI

Machine Learning

Michael L. Littman

David A. McAllester

Richard S. Sutton

Michael Collins


Input: When data are unlabelled, supervised learning is not possible, and an unsupervised learning approach is required which attempts to find natural Cluster analysis to groups, and then map new data to these formed groups.

supervised learning

unsupervised learning

Cluster analysis


Input: This field of computer science developed in the 1950s at academic institutions such as the MIT A.I. Lab, originally as a branch of artificial intelligence and robotics.

computer science

artificial intelligence

robotics

MIT A.I. Lab


Input: It could also be replaced by the Log loss equation below:

Log loss


Input: The Shirley Ryan AbilityLab (formerly the Rehabilitation Institute of Chicago), University of California at Berkeley, MIT, Stanford University, and University of Twente in the Netherlands are the researching leaders in biomechatronics.

Shirley Ryan AbilityLab

Rehabilitation Institute of Chicago

University of California at Berkeley

MIT

Stanford University

University of Twente

Netherlands

biomechatronics


Input: Given a set of predicted values and a corresponding set of actual values for X for various time periods, a common evaluation technique is to use the mean squared prediction error; other measures are also available (see forecasting #forecasting accuracy).

mean squared prediction error

forecasting accuracy


Input: Other measures, such as the proportion of correct predictions (also termed accuracy), are not useful when the two classes are of very different sizes.

accuracy


Input: The first alpha version of OpenCV was released to the public at the Conference on Computer Vision and Pattern Recognition in 2000, and five betas were released between 2001 and 2005.

OpenCV

Computer Vision and Pattern Recognition


Input: Results have been presented which give correlation of up to 0.964 with human judgement at the corpus level, compared to BLEU' s achievement of 0.817 on the same data set.

BLEU


Input: An early version of VMAF has been shown to outperform other image and video quality metrics such as SSIM, PSNR -HVS and VQM-VFD on three of four datasets in terms of prediction accuracy, when compared to subjective ratings.

VMAF

SSIM

PSNR -HVS

VQM-VFD

accuracy


Input: For example, the ambiguity of' mouse' (animal or device) is not relevant in machine translation, but is relevant in information retrieval.

machine translation

information retrieval


Input: Geometric hashing was originally suggested in computer vision for object recognition in 2D and 3D,

Geometric hashing

computer vision

object recognition


Input: It forms one of the three main categories of machine learning, along with supervised learning and reinforcement learning.

machine learning

supervised learning

reinforcement learning


Input: Reinforcement learning, due to its generality, is studied in many other disciplines, such as game, control theory, operations research, information theory, simulation-based optimization, multi-agent systems, swarm intelligence, statistics and genetic algorithm s.

Reinforcement learning

game

control theory

operations research

information theory

simulation-based optimization

multi-agent systems

swarm intelligence

statistics

genetic algorithm


Input: Pattern recognition is closely related to artificial intelligence and machine learning,

Pattern recognition

artificial intelligence

machine learning


Input: The software is used to design, train and deploy neural network (supervised learning and unsupervised learning) models to perform a wide variety of tasks such as data mining, classification, function approximation, multivariate regression and time-series prediction.

neural network

multivariate regression

supervised learning

unsupervised learning

data mining

classification

function approximation

time-series prediction


Input: In 2016, he was elected Fellow of Association for the Advancement of Artificial Intelligence.

Association for the Advancement of Artificial Intelligence


Input: She serves as a member of the National Academy of Sciences (since 2005), American Academy of Arts and Sciences (since 2009),

National Academy of Sciences

American Academy of Arts and Sciences


Input: During the 1973 Yom Kippur War, Soviet-supplied surface-to-air missile batteries in Egypt and Syria caused heavy damage Israeli fighter jet s.

Yom Kippur War

Israeli

surface-to-air missile

Egypt

Syria


Input: Another resource (free but copyrighted) is the HTK book (and the accompanying HTK toolkit).

HTK book

HTK toolkit


Input: - were taken in the 2004 AAAI Spring Symposium where linguists, computer scientists, and other interested researchers first aligned interests and proposed shared tasks and benchmark data sets for the systematic computational research on affect, appeal, subjectivity, and sentiment in text.

2004 AAAI


Input: A single grid can be analysed for both content (eyeball inspection) and structure (cluster analysis, principal component analysis, and a variety of structural indices relating to the complexity and range of the ratings being the chief techniques used).

eyeball inspection

cluster analysis

principal component analysis


Input: In 2018 Toyota was regarded as being behind in Self-driving car and in need of innovation.

Toyota

Self-driving car


Input: Such targets include natural objects such as ground, sea, precipitation (such as rain, snow or hail), sand storm s, animals (especially birds), atmospheric turbulence, and other atmospheric effects, such as ionosphere reflections, meteor trails, and three body scatter spike.

ionosphere reflections

meteor trails

three body scatter spike


Input: In planning and control, the essential difference between humanoids and other kinds of robots (like industrial ones) is that the movement of the robot must be human-like, using legged locomotion, especially biped gait.

industrial

biped gait


Input: The gradient descent can take many iterations to compute a local minimum with a required accuracy, if the curvature in different directions is very different for the given function.

gradient descent

local minimum

curvature

accuracy


Input: The 1997 RoboCup 2D Soccer Simulation League was the first RoboCup competition promoted in conjunction with International Joint Conference on Artificial Intelligence held in Nagoya, Japan, from 23 to 29 August 1997.

1997 RoboCup 2D Soccer Simulation League

RoboCup

International Joint Conference on Artificial Intelligence

Nagoya

Japan


Input: Other programming options include an embedded Python environment, and an R Console plus support for Rserve.

Python

R

Rserve


Input: From Bonn he has contributed fundamentally to artificial intelligence and robotics (with Wolfram Burgard, Dieter Fox, Sebastian Thrun among his students), and to the development of software engineering, particularly in civil engineering, and information systems, particularly in the geosciences. won the AAAI Classic Paper award of 2016.2014.

Bonn

Wolfram Burgard

Dieter Fox

Sebastian Thrun

artificial intelligence

robotics

software engineering

civil engineering

information systems

geosciences.

AAAI Classic Paper award


Input: The first USA edition of Campus Party will take place from 20 to 22 of August at TCF Center in Detroit, Michigan.

USA edition of Campus Party

TCF Center

Detroit

Michigan


Input: Together with Yann LeCun, and Yoshua Bengio, Hinton won the 2018 Turing Award for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing.

Yann LeCun

Yoshua Bengio

Hinton

Turing Award

deep neural networks


Input: Euler Math Toolbox uses a matrix language similar to MATLAB, a system that had been under development since the 1970s.

Euler Math Toolbox

MATLAB


Input: Some languages make it possible portably (e.g. Scheme, Common Lisp, Perl or D).

Scheme

Common Lisp

Perl

D


Input: In 1969 a famous book entitled Perceptrons by Marvin Minsky and Seymour Papert showed that it was impossible for these classes of network to learn an XOR function.

Perceptrons

XOR function

Marvin Minsky

Seymour Papert


Input: Large numbers of Russian scientific and technical documents were translated using SYSTRAN under the auspices of the USAF Foreign Technology Division (later the National Air and Space Intelligence Center) at Wright-Patterson Air Force Base, Ohio.

Russian

SYSTRAN

USAF Foreign Technology Division

National Air and Space Intelligence Center

Wright-Patterson Air Force Base

Ohio


Input: Semi-supervised learning falls between unsupervised learning (without any labeled training data) and supervised learning (with completely labeled training data).

Semi-supervised learning

unsupervised learning

supervised learning


Input: An n -gram model is a type of probabilistic language model for predicting the next item in such a sequence in the form of a (n − 1) -order Markov model .efficiently.

n -gram model

probabilistic language model

Markov model


Input: The Cleveland Clinic has used Cyc to develop a natural language query interface of biomedical information, spanning decades of information on cardiothoracic surgeries.

Cleveland Clinic

Cyc

natural language query interface of biomedical information


Input: The incident strained relations between the United States and Japan, and resulted in the arrest and prosecution two senior executives, as well as the imposition of sanctions on the company by both countries.

United States

Japan


Input: If the modeling is done by an artificial neural network or other machine learning, the optimization of parameters is called training, while the optimization of model hyperparameters is called tuning and often uses cross-validation ..

artificial neural network

cross-validation

machine learning

training

tuning


Input: Localized versions of the site available in the United Kingdom, India, and Australia were discontinued following the acquisition of Rotten Tomatoes by Fandango.

United Kingdom

India

Australia

Rotten Tomatoes

Fandango


Input: The NER model is one of a number of methods for determining the accuracy of live subtitles in television broadcasts and events that are produced using speech recognition.

NER

speech recognition

accuracy


Input: Atran has taught at Cambridge University, Hebrew University in Jerusalem, the École pratique des hautes études and École Polytechnique in Paris, and John Jay College of Criminal Justice in New York City.

Atran

Cambridge University

Hebrew University

École pratique des hautes études

École Polytechnique

John Jay College of Criminal Justice

Jerusalem

Paris

New York City


Input: SHRDLU was an early natural language understanding computer program, developed by Terry Winograd at MIT in 1968-1970

SHRDLU

natural language understanding

Terry Winograd

MIT


Input: He received a B.E. in electronics engineering from B.M.S. College of Engineering in Bangalore, India in 1982, when it was affiliated with Bangalore University, an M.S. in electrical and computer engineering in 1984 from Drexel University, and an M.S. in computer science in 1989, and a Ph.D. in 1990, respectively, from the University of Wisconsin-Madison, where he studied Artificial Intelligence and worked with Leonard Uhr.

B.E.

M.S.

M.S.

Ph.D.

electronics engineering

electrical and computer engineering

computer science

Artificial Intelligence

B.M.S. College of Engineering

Bangalore University

Drexel University

University of Wisconsin-Madison

Bangalore

India

Leonard Uhr


Input: Accuracy is usually rated with word error rate (WER), whereas speed is measured with the real time factor.

word error rate

WER

real time factor


Input: In 1971 Terry Winograd developed an early natural language processing engine capable of interpreting naturally written commands within a simple rule-governed environment.

Terry Winograd

natural language processing


Input: In artificial intelligence, Marvin Minsky, Herbert A. Simon, and Allen Newell are prominent.

artificial intelligence

Marvin Minsky

Herbert A. Simon

Allen Newell


Input: In the latter half of the 20th century, electrical engineering itself separated into several disciplines, specialising in the design and analysis of systems that manipulate physical signals; electronic engineering and computer engineering as examples; while design engineering developed to deal with functional design of user-machine interfaces.

electrical engineering

electronic engineering

computer engineering

design engineering

user-machine interfaces


Input: Perhaps the simplest statistic is accuracy or Fraction Correct (FC), which measures the fraction of all instances that are correctly categorized; it is the ratio of the number of correct classifications to the total number of correct or incorrect classifications: (TP + TN) / Total Population = (TP + TN) / (TP + TN + FP + FN).

accuracy

Fraction Correct

FC

TP + TN

TP + TN

TP + TN + FP + FN


Input: In the academic community, the major forums for research started in 1995 when the First International Conference Data Mining and Knowledge Discovery (KDD-95) was started in Montreal under AAAI sponsorship.

First International Conference Data Mining and Knowledge Discovery

AAAI

Montreal


Input: In this approach, models are developed using different data mining, machine learning algorithms to predict users' rating of unrated items.

data mining

machine learning


Input: In light of the above discussion, we see that the SVM technique is equivalent to empirical risk with Tikhonov regularization, where in this case the loss function is the hinge loss

SVM

empirical risk

Tikhonov regularization

loss function

hinge loss


Input: The 2015 edition was hosted by Molly McGrath, with Chris Rose and former UFC fighter Kenny Florian as commentators.

Molly McGrath

Chris Rose

Kenny Florian

UFC


Input: A subset called Micro-Planner was implemented by Gerald Jay Sussman, Eugene Charniak and Terry Winograd Sussman,, and Winograd 1971 and was used in Winograd's natural-language understanding program SHRDLU, Eugene Charniak's story understanding work, Thorne McCarty's work on legal reasoning, and some other projects.

Micro-Planner

SHRDLU

Gerald Jay Sussman

Eugene Charniak

Terry Winograd

Sussman

Winograd

Winograd

Eugene Charniak

Thorne McCarty

natural-language understanding

story understanding

legal reasoning


Input: WordNet has been used for a number of purposes in information systems, including word-sense disambiguation, information retrieval, automatic text classification, Automatic summarization, machine translation and even automatic crossword puzzle generation.

WordNet

information systems

word-sense disambiguation

information retrieval

automatic text classification

Automatic summarization

machine translation

automatic crossword puzzle generation


Input: Keutzer was named a Fellow of the IEEE in 1996.

Keutzer

IEEE


Input: A widely used type of composition is the nonlinear weighted sum, where math \ textstyle f (x) = K \ left (\ sum _ i w _ i g _ i (x) \ right) / math, where math \ textstyle K / math (commonly referred to as the activation function) is some predefined function, such as the hyperbolic tangent, sigmoid function, softmax function, or rectifier function.

nonlinear weighted sum

hyperbolic tangent

sigmoid function

softmax function

rectifier function

activation function


Input: In the film Westworld, female robots actually engaged in intercourse with human men as part of the make-believe vacation world human customers paid to attend.

Westworld


Input: Typically, the process starts by terminology extraction and concepts or noun phrase s from plain text using linguistic processors such as part-of-speech tagging and phrase chunking.

terminology extraction

part-of-speech tagging

phrase chunking


Input: They demonstrated its performance on a number of problems of interest to the machine learning community, including handwriting recognition.

machine learning

handwriting recognition


Input: While studying at Stanford, Scheinman was awarded a fellowship sponsored by George Devol, the inventor of the Unimate, the first industrial robot.

Stanford

Scheinman

George Devol

Unimate

industrial robot


Input: While originally used to evaluate machine translations, bilingual evaluation understudy (BLEU) has been used successfully to evaluate paraphrase generation models as well.

machine translations

bilingual evaluation understudy

BLEU

paraphrase generation models


Input: Unimation later licensed their technology to Kawasaki Heavy Industries and GKN, manufacturing Unimate s in Japan and England respectively.

Unimation

Kawasaki Heavy Industries

GKN

Unimate

Japan

England


Input: Much of the confusion between these two research communities (which do often have separate conferences and separate journals, ECML PKDD being a major exception) comes from the basic assumptions they work with: in machine learning, performance is usually evaluated with respect to the ability to reproduce known knowledge, while in knowledge discovery and data mining (KDD) the key task is the discovery of previously unknown knowledge.

ECML PKDD

knowledge discovery and data mining

KDD

machine learning


Input: Hidden Markov model s are the basis for most modern automatic speech recognition systems.

Hidden Markov model

automatic speech recognition systems


Input: , a company in Bangalore, India specializing in online handwriting recognition software.

Bangalore

India

handwriting recognition


Input: Do repeated translations converge on a single expression in both languages? I.e. does the translation method show stationarity or produce a canonical form? Does the translation become stationary without losing the original meaning? This metric has been criticized as not being well correlated with BLEU (BiLingual Evaluation Understudy) scores.

canonical form

BLEU

BiLingual Evaluation Understudy


Input: He holds fellowships in the American Association for Artificial Intelligence, the Center for Advanced Study in the Behavioral Sciences at Stanford University, the MIT Center for Cognitive Science, the Canadian Institute for Advanced Research, the Canadian Psychological Association, and was elected Fellow of the Royal Society of Canada in 1998.

American Association for Artificial Intelligence

Center for Advanced Study in the Behavioral Sciences

Canadian Institute for Advanced Research

Canadian Psychological Association

Royal Society of Canada

Stanford University

MIT

Cognitive Science


Input: Hinton - together with Yoshua Bengio and Yann LeCun - are referred to by some as the Godfathers of AI and Godfathers of Deep Learning.

Hinton

Yoshua Bengio

Yann LeCun

Godfathers of AI

Godfathers of Deep Learning


Input: The lightweight open-source speech project eSpeak, which has its own approach to synthesis, has experimented with Mandarin and Cantonese. eSpeak was used by Google Translate from May 20102010.

eSpeak

eSpeak

Google Translate

Mandarin

Cantonese.


Input: Also released in 1982, Software Automatic Mouth was the first commercial all-software voice synthesis program.

Software Automatic Mouth

synthesis program


Input: The column ratios are TRUE Positive Rate (TPR, aka Sensitivity or recall) (TP / (TP + FN)), with complement the FALSE Negative Rate (FNR) (FN / (TP + FN)); and TRUE Negative Rate (TNR, aka Specificity, SPC) (TN / (TN + FP)), with complement FALSE Positive Rate (FPR) (FP / (TN + FP)).

TRUE Positive Rate

TPR

Sensitivity

recall

TP / (TP + FN)

FALSE Negative Rate

FNR

FN / (TP + FN)

TRUE Negative Rate

TNR

Specificity

SPC

TN / (TN + FP)

FALSE Positive Rate

FPR

FP / (TN + FP)


Input: Edsinger and Weber collaborated on many other robots as well, and their experience working with the Kismet

Edsinger

Weber

Kismet


Input: R functionality is accessible from several scripting languages such as Python, are available as well.

R

Python


Input: VAL was one of the first robot languages and was used in Unimate robots.

VAL

Unimate robots


Input: They presented their database for the first time as a poster at the 2009 Conference on Computer Vision and Pattern Recognition (CVPR) in Florida.

2009 Conference on Computer Vision and Pattern Recognition

CVPR

Florida


Input: Categorization tasks in which no labels are supplied are referred to as unsupervised classification, unsupervised learning, Cluster analysis.

Categorization tasks

unsupervised classification

Cluster analysis

unsupervised learning


Input: It needs to Object recognition, recognize and locate humans and further emotion recognition.

Object recognition

emotion recognition


Input: The process is complex and contains encoding and recall or retrieval.

encoding

recall

retrieval


Input: Also known as parallel robots, or generalized Stewart platforms (in the Stewart platform, the actuators are paired together on both the basis and the platform), these systems are articulated robot s that use similar mechanisms for the movement of either the robot on its base, or one or more manipulator arms.

Stewart platforms

Stewart platform

articulated robot


Input: Machine vision as a systems engineering discipline can be considered distinct from computer vision, a form of computer science.

Machine vision

systems engineering

computer vision

computer science


Input: The activation function of the LSTM gates is often the logistic sigmoid function.

LSTM gates

logistic sigmoid function


Input: In other words, the sample mean is the (necessarily unique) efficient estimator, and thus also the minimum variance unbiased estimator (MVUE), in addition to being the maximum likelihood estimator.

sample mean

minimum variance unbiased estimator

MVUE

maximum likelihood estimator


Input: The 2001 Scientific American article by Berners-Lee, James Hendler, and Ora Lassila described an expected evolution of the existing Web to a Semantic Web.

Scientific American

Berners-Lee

James Hendler

Ora Lassila

Web

Semantic Web


Input: Blade Runner used a number of then-lesser-known actors: Sean Young portrays Rachael, an experimental replicant implanted with the memories of Tyrell's niece, causing her to believe she is human; Sammon, pp. 92-93 Nina Axelrod auditioned for the role.

Blade Runner

Sean Young

Rachael

Tyrell

Sammon

Nina Axelrod


Input: Gerry Sussman, Eugene Charniak, Seymour Papert and Terry Winograd visited the University of Edinburgh in 1971 spreading the news about Micro-Planner and SHRDLU and casting doubt on the resolution uniform proof procedure approach that had been the mainstay of the Edinburgh Logicists.

Gerry Sussman

Eugene Charniak

Seymour Papert

Terry Winograd

University of Edinburgh

Micro-Planner

SHRDLU

Edinburgh


Input: Walter's work inspired subsequent generations of robotics researchers such as Rodney Brooks, Hans Moravec and Mark Tilden.

Walter

Rodney Brooks

Hans Moravec

Mark Tilden

robotics


Input: Subsequently, a similar GPU-based CNN by Alex Krizhevsky et al. won the ImageNet Large Scale Visual Recognition Challenge 2012.

CNN

Alex Krizhevsky

ImageNet Large Scale Visual Recognition Challenge 2012


Input: Commonly used loss functions for probabilistic classification include log loss and the Brier score between the predicted and the TRUE probability distributions.

loss functions

TRUE probability

log loss

Brier score


Input: In May 2016, NtechLab was admitted to the official testing of biometrics technology by NIST among the three Russian companies.

NtechLab

NIST

biometrics

Russian


Input: However, floating-point numbers have only a certain amount of mathematical precision.


Input: During 2015, many of SenseTime's papers were accepted into the Conference on Computer Vision and Pattern Recognition (CVPR).

SenseTime

Conference on Computer Vision and Pattern Recognition

CVPR


Input: He co-developed optimal algorithms for Structure From Motion (SFM, or Visual SLAM, simultaneous localization and mapping, in Robotics; Best Paper Award at Conference on Computer Vision and Pattern Recognition 1998), characterized its ambiguities (David Marr Prize at ICCV 1999), also characterized the identifiability and observability of visual-inertial sensor fusion (Best Paper Award at Robotics 2015).

Structure From Motion

SFM

Visual SLAM

simultaneous localization and mapping

Robotics

Robotics

Best Paper Award

David Marr Prize

Best Paper Award

Conference on Computer Vision and Pattern Recognition

ICCV 1999


Input: Stephen H. Muggleton FBCS, FIET, Association for the Advancement of Artificial Intelligence,

Stephen H. Muggleton

FBCS

FIET

Association for the Advancement of Artificial Intelligence


Input: Edge detection is a fundamental tool in image processing, machine vision and computer vision, particularly in the areas of feature detection and feature extraction.

Edge detection

feature detection

feature extraction

image processing

machine vision

computer vision


Input: An example of this would be a variable such as outside temperature (mathtemp / math), which in a given application might be recorded to several decimal places of precision (depending on the sensing apparatus).

outside temperature

decimal places of precision


Input: The returning judges are Fon Davis, Jessica Chobot, and Leland Melvin, as well as celebrity guest judges actor Clark Gregg, MythBusters host and former Battlebots builder Adam Savage, NFL tightend Vernon Davis, and YouTube star Michael Stevens a.k.a. Vsauce.

Fon Davis

Jessica Chobot

Leland Melvin

Clark Gregg

Adam Savage

Vernon Davis

Michael Stevens

Vsauce

MythBusters

Battlebots

NFL

YouTube


Input: But these methods never won over the non-uniform internal-handcrafting Gaussian mixture model / Hidden Markov model (GMM-HMM) technology based on generative models of speech trained discriminatively.

Gaussian mixture model

Hidden Markov model

GMM-HMM


Input: Software packages like MATLAB, GNU Octave, Scilab, and SciPy provide convenient ways to apply these different methods.

MATLAB

SciPy

GNU Octave

Scilab


Input: Linear predictive coding (LPC), a speech processing algorithm, was first proposed by Fumitada Itakura of Nagoya University and Shuzo Saito of Nippon Telegraph and Telephone (NTT) in 1966.

Linear predictive coding

LPC

speech processing

Fumitada Itakura

Shuzo Saito

Nagoya University

Nippon Telegraph and Telephone

NTT


Input: In 2006, for the 25th anniversary of the algorithm, a workshop was organized at the International Conference on Computer Vision and Pattern Recognition (CVPR) to summarize the most recent contributions and variations to the original algorithm, mostly meant to improve the speed of the algorithm, the robustness and accuracy of the estimated solution and to decrease the dependency from user defined constants.

International Conference on Computer Vision and Pattern Recognition

CVPR


Input: The members went to the University of Debrecen, the Hungarian Academy of Sciences, Eötvös Loránd University, etc.

University of Debrecen

Eötvös Loránd University

Hungarian Academy of Sciences


Input: To extend SVM to cases in which the data are not linearly separable, we introduce the loss function,

SVM

loss function


Input: Logo is an educational programming language, designed in 1967 by Wally Feurzeig, Seymour Papert, and Cynthia Solomon.

Logo

Wally Feurzeig

Seymour Papert

Cynthia Solomon


Input: Eyring Research Institute was instrumental to the U.S. Air Force Missile Directorate at Hill Air Force Base near Ogden, Utah to produce in top military secrecy, the Intelligent Systems Technology Software that was foundational to the later named Reagan Star Wars program.

Eyring Research Institute

U.S. Air Force Missile Directorate

Hill Air Force Base

Ogden

Utah

Intelligent Systems Technology Software

Reagan Star Wars program


Input: Over the decades he has researched and developed emerging fields of computer science from compiler, programming languages and system architecture John F. Sowa and John Zachman (1992).

computer science

John F. Sowa

John Zachman


Input: The Sobel operator, sometimes called the Sobel-Feldman operator or Sobel filter, is used in image processing and computer vision, particularly within edge detection algorithms where it creates an image emphasising edges.

Sobel operator

Sobel-Feldman operator

Sobel filter

image processing

computer vision

edge detection algorithms


Input: LDA is a supervised learning algorithm that utilizes the labels of the data, while PCA is an learning algorithm that ignores the labels.

LDA

PCA

supervised learning


Input: Other linear classification algorithms include Winnow, support vector machine and logistic regression.

Winnow

support vector machine

logistic regression


Input: VTK consists of a C + + class library and several interpreted interface layers including Tcl / Tk, Java, and Python.

VTK

Tcl / Tk

C + +

Java

Python


Input: Also, text produced by processing spontaneous speech using automatic speech recognition and printed or handwritten text using optical character recognition contains processing noise.

automatic speech recognition

optical character recognition


Input: Miller wrote several books and directed the development of WordNet, an online word-linkage database usable by computer programs.

Miller

WordNet


Input: Contemporary automata are represented by the works of Cabaret Mechanical Theatre in the United Kingdom, Dug North and Chomick + Meder, Arthur Ganson, Joe Jones in the United States, Le Défenseur du Temps by French artist Jacques Monestier, and François Junod in Switzerland.

automata

Cabaret Mechanical Theatre

United Kingdom

United States

Switzerland

Dug North

Chomick + Meder

Arthur Ganson

Joe Jones

Jacques Monestier

François Junod

Le Défenseur du Temps

French


Input: MATLAB does include standard codefor / code and codewhile / code loops, but (as in other similar applications such as R), using the vectorized notation is encouraged and is often faster to execute.

MATLAB

R


Input: Pausch received two awards from Association for Computing Machinery in 2007 for his achievements in computing education: the Karl V. Karlstrom Outstanding Educator Award and the ACM SIGCSE Award for Outstanding Contributions to Computer Science Education.

Pausch

Association for Computing Machinery

computing education

Karl V. Karlstrom Outstanding Educator Award

ACM SIGCSE Award for Outstanding Contributions to Computer Science Education


Input: In 1960, Devol personally sold the first Unimate robot, which was shipped in 1961 to General Motors.

Devol

Unimate

robot

General Motors


Input: Semantic networks are used in natural language processing applications such as semantic parsing.

Semantic networks

natural language processing

semantic parsing


Input: Some successful applications of deep learning are computer vision and speech recognition. Honglak Lee, Roger Grosse, Rajesh Ranganath, Andrew Y. Ng.

deep learning

computer vision

speech recognition

Honglak Lee

Roger Grosse

Rajesh Ranganath

Andrew Y. Ng


Input: In addition to maintaining the Discovery One spacecraft systems during the interplanetary mission to Jupiter (or Saturn in the novel), HAL is capable of speech synthesis, speech recognition, facial recognition, natural language processing, lip reading, art appreciation, Affective computing, automated reasoning, spacecraft piloting and playing chess.

Discovery One spacecraft systems

HAL

Jupiter

Saturn

speech synthesis

speech recognition

facial recognition

lip reading

Affective computing

automated reasoning

spacecraft piloting

playing chess

natural language processing

art appreciation


Input: Dr. Julesz emigrated from Hungary to the United States following the 1956 Soviet invasion.

Dr. Julesz

Hungary

the United States

Soviet


Input: Sigmoid function activation functions use a second non-linearity for large inputs: math \ phi (v _ i) = (1 + \ exp (-v _ i)) ^ {-1} / math.

Sigmoid function


Input: These probabilities are used to determine what the target is using a maximum likelihood decision.

maximum likelihood decision


Input: In 1984 he moved to the University of Konstanz and in 1990 to the University of Salzburg.

University of Konstanz

University of Salzburg


Input: Some popular fitness functions based on the confusion matrix include sensitivity / specificity, recall / precision, F-measure, Jaccard similarity, Matthews correlation coefficient, and cost / gain matrix which combines the costs and gains assigned to the 4 different types of classifications.

confusion matrix

sensitivity / specificity

recall / precision

F-measure

Jaccard similarity

Matthews correlation coefficient

cost / gain matrix


Input: Common numerical programming environments such as MATLAB, SciLab, NumPy, Sklearn and the R language provide some of the simpler feature extraction techniques (e.g. principal component analysis) via built-in commands.

MATLAB

SciLab

NumPy

Sklearn

R language

principal component analysis


Input: Industrial robots have been implemented to collaborate with humans to perform industrial manufacturing tasks.

Industrial robots


Input: In the first published paper on CGs, John F. Sowa applied them to a wide range of topics in artificial intelligence, computer science, and cognitive science.

CGs

artificial intelligence

computer science

cognitive science

John F. Sowa


Input: NIST also differs from BLEU in its calculation of the brevity penalty, insofar as small variations in translation length do not impact the overall score as much.

NIST

BLEU

brevity penalty


Input: The IJCAI Award for Research Excellence is a biannual award given at the IJCAI conference to researcher in artificial intelligence as a recognition of excellence of their career.

IJCAI Award for Research Excellence

IJCAI

artificial intelligence


Input: Lenat was one of the original Fellows of the AAAI, and is the only individual to have on the Scientific Advisory Boards of both Microsoft and Apple.

Lenat

AAAI

Scientific Advisory Boards of both Microsoft and Apple


Input: Autoencoders are trained to minimise reconstruction errors (such as Mean squared error), often referred to as the loss:

Autoencoders

Mean squared error

loss


Input: An alternative to the use of the definitions is to consider general word-sense relatedness and to compute the similarity of each pair of word senses based on a given lexical knowledge base such as WordNet.

lexical knowledge base

WordNet


Input: TD-Lambda is a learning algorithm invented by Richard S. Sutton based on earlier work on temporal difference learning by Arthur Samuel.

TD-Lambda

Richard S. Sutton

Arthur Samuel


Input: In data mining and statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis which seeks to build a hierarchy of clusters.

data mining

statistics

hierarchical clustering

hierarchical cluster analysis

HCA

cluster analysis


Input: The concept of deconvolution is widely used in the techniques of signal processing and image processing.

deconvolution

signal processing

image processing


Input: Cognitive maps serve the construction and accumulation of spatial knowledge, allowing the mind's eye to visualize images in order to reduce cognitive load, enhance recall and learning of information.

Cognitive maps

cognitive load

recall


Input: , typically providing bindings to languages such as Python, C + +, Java).

Python

C + +

Java


Input: A voice-user interface (VUI) makes spoken human interaction with computers possible, using speech recognition to understand spoken commands and Question answering, and typically text to speech to play a reply.

voice-user interface

VUI

speech recognition

Question answering

text to speech


Input: Jess is a rule engine for the Java platform that was developed by Ernest Friedman-Hill of Sandia National.

Jess

Java

rule engine

Ernest Friedman-Hill

Sandia National


Input: For multilayer perceptron s, where a hidden layer exists, more sophisticated algorithms such as backpropagation must be used.

multilayer perceptron

backpropagation


Input: Google Translate's neural machine translation system uses a large end-to-end artificial neural network that attempts to perform deep learning, in particular, long short-term memory networks.

Google Translate

neural machine translation system

end-to-end artificial neural network

long short-term memory networks

deep learning


Input: Various methods for doing so were developed in the 1980s and early 1990s by Werbos, Williams, Robinson, Jürgen Schmidhuber, Sepp Hochreiter, Pearlmutter and others.

Werbos

Williams

Robinson

Jürgen Schmidhuber

Sepp Hochreiter

Pearlmutter


Input: | Apple Apple Inc originally licensed software from Nuance to provide speech recognition capability to its digital assistant Siri.

Apple

Apple Inc

Nuance

speech recognition

Siri


Input: Columbia released several 3D westerns produced by Sam Katzman and directed by William Castle.

Columbia

3D westerns

Sam Katzman

William Castle


Input: It incorporates knowledge and research in the computer science, linguistics and computer engineering fields.

computer science

linguistics

computer engineering


Input: Here is an example of R code:

R


Input: The ROC curve is created by plotting the TRUE positive rate (TPR) against the FALSE positive rate (FPR) at various threshold settings.

ROC curve

TRUE positive rate

TPR

FALSE positive rate

FPR


Input: Research stagnated after machine learning research by Marvin Minsky and Seymour Papert (1969),

machine learning

Marvin Minsky

Seymour Papert


Input: Other programming environments that are used to build DAQ applications include ladder logic, Visual C + +, Visual Basic, LabVIEW, and MATLAB.

DAQ

ladder logic

Visual Basic

Visual C + +

LabVIEW

MATLAB


Input: The metric was designed to fix some of the problems found in the more popular BLEU metric, and also produce good correlation with human judgement at the sentence or segment level.

BLEU metric


Input: Techniques such as dynamic Markov Networks, Convolutional neural network and Long short-term memory are often employed to exploit the semantic correlations between consecutive video frames.

dynamic Markov Networks

Convolutional neural network

Long short-term memory


Input: Mass-produced printed circuit board s (PCBs) are almost exclusively manufactured by pick-and-place robots, typically with SCARA manipulators, which remove tiny electronic component s from strips or trays, and place them on to PCBs with great accuracy.

printed circuit board

PCBs

pick-and-place robots

SCARA

PCBs


Input: In the context of machine learning, where it is most widely applied today, LDA was rediscovered independently by David Blei, Andrew Ng and Michael I. Jordan in 2003, and presented as a graphical model for topic discovery.

machine learning

LDA

graphical model

David Blei

Andrew Ng

Michael I. Jordan

topic discovery


Input: The measured performance on test data of eight naive WSI across various tauopathies resulted in the recall, precision, and an F1 score of 0.92, 0.72, and 0.81, respectively.

WSI

tauopathies

recall

precision

F1 score


Input: With the help of advanced AR technologies (e.g. adding computer vision, incorporating AR cameras into smartphone and object recognition) the information about the surrounding real world of the user becomes interactive and digitally manipulated.

AR

computer vision

AR

object recognition


Input: In 2014, Schmidhuber formed a company, Nnaisense, to work on commercial applications of artificial intelligence in fields such as finance, heavy industry and self-driving car s.

Schmidhuber

Nnaisense

artificial intelligence

self-driving car


Input: Not only does this alter the performance of all subsequent tests on the retained explanatory model, it may introduce bias and alter mean square error in estimation.

mean square error


Input: Bigrams are used in most successful language model s for speech recognition.

Bigrams

language model

speech recognition


Input: His research in cognitive psychology has won the Early Career Award (1984) and Boyd McCandless Award 1986) from the American Psychological Association, the Troland Research Award (1993) from the National Academy of Sciences, the Henry Dale Prize (2004) from the Royal Institution of Great Britain, and the George Miller Prize (2010) from the Cognitive Neuroscience Society.

cognitive psychology

Early Career Award

Boyd McCandless Award

Troland Research Award

Henry Dale Prize

George Miller Prize

American Psychological Association

National Academy of Sciences

Royal Institution of Great Britain

Cognitive Neuroscience Society


Input: An eigenface (The approach of using eigenfaces for Facial recognition system was developed by Sirovich and Kirby (1987) and used by Matthew Turk and Alex Pentland in face classification. Turk, Matthew A and Pentland, Alex P. Face recognition using eigenfaces.

eigenface

eigenfaces

eigenfaces

Facial recognition system

Sirovich

Kirby

Matthew Turk

Alex Pentland

Turk, Matthew A

Pentland, Alex P.

face classification

Face recognition


Input: A lexical dictionary such as WordNet can then be used for understanding the context.

WordNet


Input: Hyponymy is the most frequently encoded relation among synsets used in lexical databases such as WordNet.

Hyponymy

synsets

WordNet


Input: OPeNDAP offers open-source libraries in C + + and Java, but many clients rely on community developed libraries such as libraries include embedded capabilities for retrieving (array-style) data from DAP servers.

OPeNDAP

C + +

Java

DAP


Input: In that page, Samurai Damashii exaggerated the Senkousha as the crystallization of China's four thousand years of scientific knowledge, commented on the crude design (e.g. the Chinese Cannon on its crotch), and put its image among images of Honda' s ASIMO and Sony' s QRIO SDR-3X for juxtaposition.

Samurai Damashii

Chinese Cannon

Senkousha

ASIMO

QRIO SDR-3X

China

Honda

Sony


Input: There are also many programming libraries that contain neural network functionality and that can be used in custom implementations (such as TensorFlow, Theano, etc.

neural network

TensorFlow

Theano


Input: He is a Fellow of the Association for Computing Machinery, IEEE, American Association for the Advancement of Science, IAPR and SPIE.

Association for Computing Machinery

American Association for the Advancement of Science

IAPR

SPIE

IEEE


Input: A trial by RET in 2011 with Facial recognition system cameras mounted on trams made sure that people were banned from the city trams did not sneak on anyway.

RET

Facial recognition system


Input: The film, adapted from the popular Cole Porter Broadway musical, starred the MGM songbird team of Howard Keel and Kathryn Grayson as the leads, supported by Ann Miller, Keenan Wynn, Bobby Van, James Whitmore, Kurt Kasznar and Tommy Rall.

Cole Porter

Howard Keel

Kathryn Grayson

Ann Miller

Keenan Wynn

Bobby Van

James Whitmore

Kurt Kasznar

Tommy Rall

Broadway


Input: Such applications should streamline the call flows, minimize prompts, eliminate unnecessary iterations and allow elaborate mixed initiative dialog system, which enable callers to enter several pieces of information in a single utterance and in any order or combination.

mixed initiative dialog system


Input: As such, traditional gradient descent (or Stochastic gradient descent) methods can be adapted, where of taking a step in the direction of the function's gradient, a step is taken in the direction of a vector selected from the function's sub-gradient.

gradient descent

Stochastic gradient descent


Input: If it is assumed that distortion is measured by mean squared error, the distortion D, is given by:

mean squared error

distortion D


Input: MLPs were a popular machine learning solution in the 1980s, finding applications in diverse fields such as speech recognition, image recognition, and machine translation software, Neural networks.

MLPs

machine learning

speech recognition

image recognition

machine translation

Neural networks


Input: Allen received his Ph.D. from the University of Toronto in 1979, under the supervision of C. Raymond Perrault,

Allen

C. Raymond Perrault

University of Toronto


Input: OpenCV supports some models from deep learning frameworks like TensorFlow, Torch, PyTorch (after converting to an ONNX model) and Caffe according to a defined list of supported layers.

OpenCV

TensorFlow

Torch

PyTorch

ONNX

Caffe

deep learning


Input: Previously, Christensen was the Founding Chairman of European Robotics Research Network (EURON) and an IEEE Robotics and Automation Society Distinguished Lecturer in Robotics.

Christensen

European Robotics Research Network

EURON

IEEE Robotics and Automation Society

Robotics


Input: He received his master's degree in mathematics from the Samarkand State University, Samarkand, Uzbek Soviet Socialist Republic in 1958 and Ph.D in statistics at the Institute of Control Sciences, Moscow in 1964.

mathematics

statistics

Samarkand State University

Samarkand

Moscow

Uzbek Soviet Socialist Republic

Ph.D

Institute of Control Sciences


Input: Increasingly, however, work at Cycorp involves giving the Cyc system the ability to communicate with end users in natural language, and to assist with the ongoing knowledge formation process via machine learning and natural language understanding.

Cycorp

Cyc system

machine learning

natural language understanding


Input: For example, if the most suitable classifier for the problem is sought, the training dataset is used to train the candidate algorithms, the validation dataset is used to compare their performances and decide which one to take and, finally, the test dataset is used to obtain the performance characteristics such as accuracy, sensitivity, specificity, F-measure, and so on.

accuracy

sensitivity

specificity

F-measure


Input: The Mean squared error is 0.15.

Mean squared error


Input: In 1979 a Micromouse competition was organized by the IEEE as shown in the Spectrum magazine.

Micromouse competition

Spectrum

IEEE


Input: The Gabor space is very useful in image processing applications such as optical character recognition, iris recognition and fingerprint recognition.

Gabor space

image processing

optical character recognition

iris recognition

fingerprint recognition


Input: or via high-level interfaces to Java and Tcl.

Java

Tcl


Input: In recent research, kernel-based methods such as support vector machine s have shown superior performance in supervised.

support vector machine

supervised


Input: To illustrate the basic principles of bagging, below is an analysis on the relationship between ozone and temperature (data from Rousseeuw and Leroy (1986), analysis done in R).

ozone

Rousseeuw

Leroy

R


Input: Denso Wave is a subsidiary that produces automatic identification products (bar-code reader s and related products), industrial robot s and programmable logic controller s.

Denso Wave

bar-code reader

industrial robot

programmable logic controller


Input: Where Bilingual evaluation understudy simply calculates n-gram precision adding equal weight to each one, NIST also calculates how informative a particular n-gram is.

Bilingual evaluation understudy

n-gram precision

NIST

n-gram