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2101.10964
Oren Neumann
Oren Neumann, Claudius Gros
Investment vs. reward in a competitive knapsack problem
null
Learning Meets Combinatorial Algorithms at NeurIPS2020 (2020)
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Natural selection drives species to develop brains, with sizes that increase with the complexity of the tasks to be tackled. Our goal is to investigate the balance between the metabolic costs of larger brains compared to the advantage they provide in solving general and combinatorial problems. Defining advantage as t...
[ { "created": "Tue, 26 Jan 2021 17:47:56 GMT", "version": "v1" } ]
2021-01-28
[ [ "Neumann", "Oren", "" ], [ "Gros", "Claudius", "" ] ]
2101.10977
Lukas Brunke
Lukas Brunke, Prateek Agrawal, Nikhil George
Evaluating Input Perturbation Methods for Interpreting CNNs and Saliency Map Comparison
null
ECCV 2020: Computer Vision - ECCV 2020 Workshops pp 120-134
10.1007/978-3-030-66415-2_8
null
cs.LG cs.CV
http://creativecommons.org/licenses/by/4.0/
Input perturbation methods occlude parts of an input to a function and measure the change in the function's output. Recently, input perturbation methods have been applied to generate and evaluate saliency maps from convolutional neural networks. In practice, neutral baseline images are used for the occlusion, such th...
[ { "created": "Tue, 26 Jan 2021 18:11:06 GMT", "version": "v1" } ]
2021-01-27
[ [ "Brunke", "Lukas", "" ], [ "Agrawal", "Prateek", "" ], [ "George", "Nikhil", "" ] ]
2101.11002
Evan Debenham
Evan R.M. Debenham and Roberto Solis-Oba (The University of Western Ontario, Canada)
New Algorithms for Computing Field of Vision over 2D Grids
Presented at the 6th International Conference on Computer Science, Engineering And Applications (CSEA 2020) 18 pages, 11 figures, 4 tables
6th International Conference on Computer Science, Engineering And Applications (CSEA 2020), Volume 10, Number 18, December 2020, pg. 1-18
null
null
cs.CV
http://creativecommons.org/licenses/by-sa/4.0/
The aim of this paper is to propose new algorithms for Field of Vision (FOV) computation which improve on existing work at high resolutions. FOV refers to the set of locations that are visible from a specific position in a scene of a computer game. We summarize existing algorithms for FOV computation, describe thei...
[ { "created": "Tue, 26 Jan 2021 20:38:35 GMT", "version": "v1" } ]
2021-01-28
[ [ "Debenham", "Evan R. M.", "", "The University of Western\n Ontario, Canada" ], [ "Solis-Oba", "Roberto", "", "The University of Western\n Ontario, Canada" ] ]
2101.11023
Taro Sakurai
Taro Sakurai (Chiba University)
On formal concepts of random formal contexts
7 pages, 2 figures, 1 table
Information Sciences 578 (2021) 615-620
10.1016/j.ins.2021.07.065
null
cs.AI cs.DS math.CO
http://creativecommons.org/licenses/by/4.0/
In formal concept analysis, it is well-known that the number of formal concepts can be exponential in the worst case. To analyze the average case, we introduce a probabilistic model for random formal contexts and prove that the average number of formal concepts has a superpolynomial asymptotic lower bound.
[ { "created": "Tue, 26 Jan 2021 19:00:06 GMT", "version": "v1" } ]
2021-08-02
[ [ "Sakurai", "Taro", "", "Chiba University" ] ]
2101.11060
Xinwei Zhao
Xinwei Zhao and Matthew C. Stamm
Defenses Against Multi-Sticker Physical Domain Attacks on Classifiers
null
This paper is published on European Conference on Computer Vision 2020, page 202-219, Springer
null
null
cs.CR cs.CV
http://creativecommons.org/licenses/by/4.0/
Recently, physical domain adversarial attacks have drawn significant attention from the machine learning community. One important attack proposed by Eykholt et al. can fool a classifier by placing black and white stickers on an object such as a road sign. While this attack may pose a significant threat to visual clas...
[ { "created": "Tue, 26 Jan 2021 19:59:28 GMT", "version": "v1" } ]
2021-01-28
[ [ "Zhao", "Xinwei", "" ], [ "Stamm", "Matthew C.", "" ] ]
2101.11081
Xinwei Zhao
Xinwei Zhao and Matthew C. Stamm
The Effect of Class Definitions on the Transferability of Adversarial Attacks Against Forensic CNNs
null
Published at Electronic Imaging, Media Watermarking, Security, and Forensics 2020, pp. 119-1-119-7(7)
null
null
cs.CV cs.CR cs.LG
http://creativecommons.org/licenses/by/4.0/
In recent years, convolutional neural networks (CNNs) have been widely used by researchers to perform forensic tasks such as image tampering detection. At the same time, adversarial attacks have been developed that are capable of fooling CNN-based classifiers. Understanding the transferability of adversarial attacks,...
[ { "created": "Tue, 26 Jan 2021 20:59:37 GMT", "version": "v1" } ]
2021-01-28
[ [ "Zhao", "Xinwei", "" ], [ "Stamm", "Matthew C.", "" ] ]
2101.11174
Weiwei Jiang
Weiwei Jiang, Jiayun Luo
Graph Neural Network for Traffic Forecasting: A Survey
null
Expert Systems with Applications Volume, vol. 207, 30 November 2022, 117921
10.1016/j.eswa.2022.117921
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Traffic forecasting is important for the success of intelligent transportation systems. Deep learning models, including convolution neural networks and recurrent neural networks, have been extensively applied in traffic forecasting problems to model spatial and temporal dependencies. In recent years, to model the gra...
[ { "created": "Wed, 27 Jan 2021 02:35:41 GMT", "version": "v1" }, { "created": "Mon, 15 Feb 2021 14:19:27 GMT", "version": "v2" }, { "created": "Tue, 30 Nov 2021 16:27:26 GMT", "version": "v3" }, { "created": "Tue, 22 Feb 2022 05:46:58 GMT", "version": "v4" } ]
2022-07-08
[ [ "Jiang", "Weiwei", "" ], [ "Luo", "Jiayun", "" ] ]
2101.11183
Haipeng Li
Haipeng Li, Shuaicheng Liu, Jue Wang
DeepOIS: Gyroscope-Guided Deep Optical Image Stabilizer Compensation
null
IEEE Transactions on Circuits and Systems for Video Technology ( Volume: 32, Issue: 5, May 2022)
10.1109/TCSVT.2021.3103281
21690602
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mobile captured images can be aligned using their gyroscope sensors. Optical image stabilizer (OIS) terminates this possibility by adjusting the images during the capturing. In this work, we propose a deep network that compensates the motions caused by the OIS, such that the gyroscopes can be used for image alignment...
[ { "created": "Wed, 27 Jan 2021 03:23:46 GMT", "version": "v1" }, { "created": "Tue, 4 Jul 2023 07:30:21 GMT", "version": "v2" } ]
2023-07-06
[ [ "Li", "Haipeng", "" ], [ "Liu", "Shuaicheng", "" ], [ "Wang", "Jue", "" ] ]
2101.11217
Tejas Khare
Tejas Atul Khare and Anuradha C. Phadke
Automated Crop Field Surveillance using Computer Vision
6 Pages, 10 Figures
Proceedings reference - 978-1-7281-9885-9/20/$31.00 \c{opyright}2020 IEEE
10.1109/DISCOVER50404.2020.9278072
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Artificial Intelligence is everywhere today. But unfortunately, Agriculture has not been able to get that much attention from Artificial Intelligence (AI). A lack of automation persists in the agriculture industry. For over many years, farmers and crop field owners have been facing a problem of trespassing of wild an...
[ { "created": "Wed, 27 Jan 2021 05:58:28 GMT", "version": "v1" } ]
2021-01-28
[ [ "Khare", "Tejas Atul", "" ], [ "Phadke", "Anuradha C.", "" ] ]
2101.11302
Niels van der Heijden
Niels van der Heijden, Helen Yannakoudakis, Pushkar Mishra, Ekaterina Shutova
Multilingual and cross-lingual document classification: A meta-learning approach
11 pages, 1 figure
Association for Computational Linguistics, Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021, 1966--1976
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
The great majority of languages in the world are considered under-resourced for the successful application of deep learning methods. In this work, we propose a meta-learning approach to document classification in limited-resource setting and demonstrate its effectiveness in two different settings: few-shot, cross-lin...
[ { "created": "Wed, 27 Jan 2021 10:22:56 GMT", "version": "v1" }, { "created": "Sat, 24 Apr 2021 10:24:38 GMT", "version": "v2" } ]
2021-04-27
[ [ "van der Heijden", "Niels", "" ], [ "Yannakoudakis", "Helen", "" ], [ "Mishra", "Pushkar", "" ], [ "Shutova", "Ekaterina", "" ] ]
2101.11431
Nicola Melluso
Silvia Fareri, Nicola Melluso, Filippo Chiarello, Gualtiero Fantoni
SkillNER: Mining and Mapping Soft Skills from any Text
null
Expert Systems With Applications 184 (2021) 115544
10.1016/j.eswa.2021.115544
null
cs.CL cs.IR
http://creativecommons.org/licenses/by/4.0/
In today's digital world, there is an increasing focus on soft skills. On the one hand, they facilitate innovation at companies, but on the other, they are unlikely to be automated soon. Researchers struggle with accurately approaching quantitatively the study of soft skills due to the lack of data-driven methods to ...
[ { "created": "Fri, 22 Jan 2021 11:14:05 GMT", "version": "v1" }, { "created": "Mon, 12 Jul 2021 18:12:46 GMT", "version": "v2" } ]
2021-07-14
[ [ "Fareri", "Silvia", "" ], [ "Melluso", "Nicola", "" ], [ "Chiarello", "Filippo", "" ], [ "Fantoni", "Gualtiero", "" ] ]
2101.11435
Yakup Kutlu
Apdullah Yayik, Yakup Kutlu
Online LDA based brain-computer interface system to aid disabled people
13 pages, 4 figures, Natural and Engineering Sciences
Natural and Engineering Sciences, 2017
null
null
cs.HC cs.AI
http://creativecommons.org/licenses/by/4.0/
This paper aims to develop brain-computer interface system based on electroencephalography that can aid disabled people in daily life. The system relies on one of the most effective event-related potential wave, P300, which can be elicited by oddball paradigm. Developed application has a basic interaction tool that e...
[ { "created": "Thu, 21 Jan 2021 08:17:05 GMT", "version": "v1" } ]
2021-01-28
[ [ "Yayik", "Apdullah", "" ], [ "Kutlu", "Yakup", "" ] ]
2101.11436
Yakup Kutlu
Kadir Tohma, Yakup Kutlu
Challenges Encountered in Turkish Natural Language Processing Studies
8 pages, Natural and Engineering Sciences
Natural and Engineering Sciences, 2020
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Natural language processing is a branch of computer science that combines artificial intelligence with linguistics. It aims to analyze a language element such as writing or speaking with software and convert it into information. Considering that each language has its own grammatical rules and vocabulary diversity, th...
[ { "created": "Thu, 21 Jan 2021 08:30:33 GMT", "version": "v1" } ]
2021-01-28
[ [ "Tohma", "Kadir", "" ], [ "Kutlu", "Yakup", "" ] ]
2101.11508
Olivier Rukundo
Olivier Rukundo
Effects of Image Size on Deep Learning
22 pages, 23 figures, 5 tables
Electronics 2023, 12(4), 985
10.3390/electronics12040985
null
cs.CV cs.LG eess.IV
http://creativecommons.org/licenses/by/4.0/
In this work, the best size for late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) images in the training dataset was determined to optimize deep learning training outcomes. Non-extra pixel and extra pixel interpolation algorithms were used to determine the new size of the LGE-MRI images. A novel stra...
[ { "created": "Wed, 27 Jan 2021 16:07:48 GMT", "version": "v1" }, { "created": "Mon, 26 Jul 2021 20:25:11 GMT", "version": "v2" }, { "created": "Mon, 23 May 2022 20:16:05 GMT", "version": "v3" }, { "created": "Thu, 28 Jul 2022 19:12:58 GMT", "version": "v4" }, { "c...
2023-02-20
[ [ "Rukundo", "Olivier", "" ] ]
2101.11560
Ece Calikus
Ece Calikus, Slawomir Nowaczyk, Mohamed-Rafik Bouguelia, and Onur Dikmen
Wisdom of the Contexts: Active Ensemble Learning for Contextual Anomaly Detection
null
Data Mining Knowledge Discovery (2022)
10.1007/s10618-022-00868-7
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In contextual anomaly detection, an object is only considered anomalous within a specific context. Most existing methods for CAD use a single context based on a set of user-specified contextual features. However, identifying the right context can be very challenging in practice, especially in datasets, with a large n...
[ { "created": "Wed, 27 Jan 2021 17:34:13 GMT", "version": "v1" }, { "created": "Thu, 15 Apr 2021 23:16:56 GMT", "version": "v2" }, { "created": "Mon, 24 Jan 2022 17:34:32 GMT", "version": "v3" }, { "created": "Tue, 4 Oct 2022 12:50:05 GMT", "version": "v4" } ]
2022-10-05
[ [ "Calikus", "Ece", "" ], [ "Nowaczyk", "Slawomir", "" ], [ "Bouguelia", "Mohamed-Rafik", "" ], [ "Dikmen", "Onur", "" ] ]
2101.11587
Steven Frank
Steven J. Frank
The Work of Art in an Age of Mechanical Generation
This is the author's final version; the article has been accepted for publication in Leonardo Journal
Leonardo(2022) 55(4): 378-381
10.1162/leon_a_02095
null
cs.CY cs.AI cs.CV
http://creativecommons.org/licenses/by/4.0/
Can we define what it means to be "creative," and if so, can our definition drive artificial intelligence (AI) systems to feats of creativity indistinguishable from human efforts? This mixed question is considered from technological and social perspectives. Beginning with an exploration of the value we attach to auth...
[ { "created": "Wed, 27 Jan 2021 18:32:58 GMT", "version": "v1" }, { "created": "Wed, 10 Aug 2022 19:31:02 GMT", "version": "v2" } ]
2022-08-12
[ [ "Frank", "Steven J.", "" ] ]
2101.11717
Francois Malgouyres
Adrien Gauffriau, Fran\c{c}ois Malgouyres (IMT), M\'elanie Ducoffe
Overestimation learning with guarantees
null
AAAI-21, workshop on safeAI, Feb 2021, Valence (Virtual), Spain
null
null
cs.LG cs.AI cs.NE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We describe a complete method that learns a neural network which is guaranteed to overestimate a reference function on a given domain. The neural network can then be used as a surrogate for the reference function. The method involves two steps. In the first step, we construct an adaptive set of Majoring Points. In th...
[ { "created": "Tue, 26 Jan 2021 09:06:03 GMT", "version": "v1" } ]
2021-01-29
[ [ "Gauffriau", "Adrien", "", "IMT" ], [ "Malgouyres", "François", "", "IMT" ], [ "Ducoffe", "Mélanie", "" ] ]
2101.11844
Iena Petronella Derks
Iena Petronella Derks and Alta de Waal
A Taxonomy of Explainable Bayesian Networks
null
In: Gerber A. (eds) Artificial Intelligence Research. SACAIR 2021. Communications in Computer and Information Science, vol 1342. Springer, Cham (2020)
10.1007/978-3-030-66151-9_14
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Artificial Intelligence (AI), and in particular, the explainability thereof, has gained phenomenal attention over the last few years. Whilst we usually do not question the decision-making process of these systems in situations where only the outcome is of interest, we do however pay close attention when these systems...
[ { "created": "Thu, 28 Jan 2021 07:29:57 GMT", "version": "v1" } ]
2021-01-29
[ [ "Derks", "Iena Petronella", "" ], [ "de Waal", "Alta", "" ] ]
2101.11978
Rodrigo Agerri
Elena Zotova, Rodrigo Agerri, German Rigau
Semi-automatic Generation of Multilingual Datasets for Stance Detection in Twitter
Stance detection, multilingualism, text categorization, fake news, deep learning
Expert Systems with Applications, 170 (2021), Elsevier
10.1016/j.eswa.2020.114547
null
cs.CL
http://creativecommons.org/licenses/by-nc-nd/4.0/
Popular social media networks provide the perfect environment to study the opinions and attitudes expressed by users. While interactions in social media such as Twitter occur in many natural languages, research on stance detection (the position or attitude expressed with respect to a specific topic) within the Natura...
[ { "created": "Thu, 28 Jan 2021 13:05:09 GMT", "version": "v1" } ]
2021-01-29
[ [ "Zotova", "Elena", "" ], [ "Agerri", "Rodrigo", "" ], [ "Rigau", "German", "" ] ]
2101.12047
Samuel Alexander
Samuel Alexander, Bill Hibbard
Measuring Intelligence and Growth Rate: Variations on Hibbard's Intelligence Measure
25 pages
Journal of Artificial General Intelligence 12(1), 2021
10.2478/jagi-2021-0001
null
cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
In 2011, Hibbard suggested an intelligence measure for agents who compete in an adversarial sequence prediction game. We argue that Hibbard's idea should actually be considered as two separate ideas: first, that the intelligence of such agents can be measured based on the growth rates of the runtimes of the competito...
[ { "created": "Mon, 25 Jan 2021 01:54:08 GMT", "version": "v1" } ]
2021-01-29
[ [ "Alexander", "Samuel", "" ], [ "Hibbard", "Bill", "" ] ]
2101.12072
Kashif Rasul
Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf
Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
null
Proceedings of the 38th International Conference on Machine Learning, PMLR 139:8857-8868, 2021
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
In this work, we propose \texttt{TimeGrad}, an autoregressive model for multivariate probabilistic time series forecasting which samples from the data distribution at each time step by estimating its gradient. To this end, we use diffusion probabilistic models, a class of latent variable models closely connected to s...
[ { "created": "Thu, 28 Jan 2021 15:46:10 GMT", "version": "v1" }, { "created": "Tue, 2 Feb 2021 12:32:30 GMT", "version": "v2" } ]
2021-07-09
[ [ "Rasul", "Kashif", "" ], [ "Seward", "Calvin", "" ], [ "Schuster", "Ingmar", "" ], [ "Vollgraf", "Roland", "" ] ]
2101.12102
Samuel Rivera
Deborah Weeks and Samuel Rivera
Domain Adaptation by Topology Regularization
null
SPIE Defense + Commercial Sensing, 2021
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning has become the leading approach to assisted target recognition. While these methods typically require large amounts of labeled training data, domain adaptation (DA) or transfer learning (TL) enables these algorithms to transfer knowledge from a labelled (source) data set to an unlabelled but related (ta...
[ { "created": "Thu, 28 Jan 2021 16:45:41 GMT", "version": "v1" } ]
2021-01-29
[ [ "Weeks", "Deborah", "" ], [ "Rivera", "Samuel", "" ] ]
2101.12136
Ghada Sokar
Ghada Sokar, Decebal Constantin Mocanu, Mykola Pechenizkiy
Self-Attention Meta-Learner for Continual Learning
null
20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021)
null
null
cs.LG cs.AI cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Continual learning aims to provide intelligent agents capable of learning multiple tasks sequentially with neural networks. One of its main challenging, catastrophic forgetting, is caused by the neural networks non-optimal ability to learn in non-stationary distributions. In most settings of the current approaches, t...
[ { "created": "Thu, 28 Jan 2021 17:35:04 GMT", "version": "v1" } ]
2021-01-29
[ [ "Sokar", "Ghada", "" ], [ "Mocanu", "Decebal Constantin", "" ], [ "Pechenizkiy", "Mykola", "" ] ]
2101.12446
Matthew Olson
Matthew L. Olson, Roli Khanna, Lawrence Neal, Fuxin Li, Weng-Keen Wong
Counterfactual State Explanations for Reinforcement Learning Agents via Generative Deep Learning
Full source code available at https://github.com/mattolson93/counterfactual-state-explanations
Artificial Intelligence, 2021, 103455, ISSN 0004-3702
10.1016/j.artint.2021.103455
null
cs.AI cs.HC cs.LG
http://creativecommons.org/licenses/by/4.0/
Counterfactual explanations, which deal with "why not?" scenarios, can provide insightful explanations to an AI agent's behavior. In this work, we focus on generating counterfactual explanations for deep reinforcement learning (RL) agents which operate in visual input environments like Atari. We introduce counterfact...
[ { "created": "Fri, 29 Jan 2021 07:43:41 GMT", "version": "v1" } ]
2021-02-01
[ [ "Olson", "Matthew L.", "" ], [ "Khanna", "Roli", "" ], [ "Neal", "Lawrence", "" ], [ "Li", "Fuxin", "" ], [ "Wong", "Weng-Keen", "" ] ]
2101.12463
Hao Li
Chenghao Chen and Hao Li
Robust Representation Learning with Feedback for Single Image Deraining
null
IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), 2021, pp.7742-7751
null
null
eess.IV cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A deraining network can be interpreted as a conditional generator that aims at removing rain streaks from image. Most existing image deraining methods ignore model errors caused by uncertainty that reduces embedding quality. Unlike existing image deraining methods that embed low-quality features into the model direct...
[ { "created": "Fri, 29 Jan 2021 08:20:50 GMT", "version": "v1" }, { "created": "Wed, 3 Feb 2021 05:58:20 GMT", "version": "v2" }, { "created": "Sun, 20 Jun 2021 09:42:53 GMT", "version": "v3" } ]
2021-06-22
[ [ "Chen", "Chenghao", "" ], [ "Li", "Hao", "" ] ]
2102.00322
Vaneet Aggarwal
Mayank Gupta and Lingjun Chen and Denny Yu and Vaneet Aggarwal
A Supervised Learning Approach for Robust Health Monitoring using Face Videos
The main part of the paper appeared in DFHS'20: Proceedings of the 2nd ACM Workshop on Device-Free Human Sensing; while the Supplementary did not appear in the proceedings
Proceedings of the 2nd ACM Workshop on Device-Free Human Sensing (DFHS 2020) Nov. 2020 pp. 6-10
10.1145/3427772.3429392
null
cs.CV cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Monitoring of cardiovascular activity is highly desired and can enable novel applications in diagnosing potential cardiovascular diseases and maintaining an individual's well-being. Currently, such vital signs are measured using intrusive contact devices such as an electrocardiogram (ECG), chest straps, and pulse oxi...
[ { "created": "Sat, 30 Jan 2021 22:03:16 GMT", "version": "v1" } ]
2021-02-02
[ [ "Gupta", "Mayank", "" ], [ "Chen", "Lingjun", "" ], [ "Yu", "Denny", "" ], [ "Aggarwal", "Vaneet", "" ] ]
2102.00385
Guangsheng Bao
Guangsheng Bao and Yue Zhang
Contextualized Rewriting for Text Summarization
null
AAAI 2021
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Extractive summarization suffers from irrelevance, redundancy and incoherence. Existing work shows that abstractive rewriting for extractive summaries can improve the conciseness and readability. These rewriting systems consider extracted summaries as the only input, which is relatively focused but can lose important...
[ { "created": "Sun, 31 Jan 2021 05:35:57 GMT", "version": "v1" }, { "created": "Mon, 26 Apr 2021 06:29:16 GMT", "version": "v2" } ]
2021-04-27
[ [ "Bao", "Guangsheng", "" ], [ "Zhang", "Yue", "" ] ]
2102.00515
Fatih Uysal
Fatih Uysal, F{\i}rat Hardala\c{c}, Ozan Peker, Tolga Tolunay and Nil Tokg\"oz
Classification of Shoulder X-Ray Images with Deep Learning Ensemble Models
This paper is accepted at Applied Sciences, MDPI, 2021, 11(6), 2723. Section: "Applied Biosciences and Bioengineering". Special Issue: "Advancing Biomedical Image Retrieval and Classification for Computer Aided Diagnosis"
Applied Sciences, MDPI, 2021, 11(6), 2723. Section: "Applied Biosciences and Bioengineering". Special Issue: "Advancing Biomedical Image Retrieval and Classification for Computer Aided Diagnosis"
10.3390/app11062723
null
eess.IV cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
Fractures occur in the shoulder area, which has a wider range of motion than other joints in the body, for various reasons. To diagnose these fractures, data gathered from Xradiation (X-ray), magnetic resonance imaging (MRI), or computed tomography (CT) are used. This study aims to help physicians by classifying shou...
[ { "created": "Sun, 31 Jan 2021 19:20:04 GMT", "version": "v1" }, { "created": "Mon, 1 Mar 2021 12:09:24 GMT", "version": "v2" }, { "created": "Sat, 20 Mar 2021 18:28:30 GMT", "version": "v3" } ]
2021-03-23
[ [ "Uysal", "Fatih", "" ], [ "Hardalaç", "Fırat", "" ], [ "Peker", "Ozan", "" ], [ "Tolunay", "Tolga", "" ], [ "Tokgöz", "Nil", "" ] ]
2102.00760
Vivien Cabannes
Vivien Cabannes and Alessandro Rudi and Francis Bach
Fast rates in structured prediction
14 main pages, 3 main figures, 43 pages, 4 figures (with appendix)
Conference on Learning Theory, PMLR 134, 2021
null
null
stat.ML cs.AI cs.LG math.ST stat.TH
http://creativecommons.org/licenses/by/4.0/
Discrete supervised learning problems such as classification are often tackled by introducing a continuous surrogate problem akin to regression. Bounding the original error, between estimate and solution, by the surrogate error endows discrete problems with convergence rates already shown for continuous instances. Ye...
[ { "created": "Mon, 1 Feb 2021 10:50:04 GMT", "version": "v1" }, { "created": "Tue, 8 Jun 2021 13:02:31 GMT", "version": "v2" }, { "created": "Thu, 15 Jul 2021 15:04:41 GMT", "version": "v3" } ]
2021-07-16
[ [ "Cabannes", "Vivien", "" ], [ "Rudi", "Alessandro", "" ], [ "Bach", "Francis", "" ] ]
2102.00838
Rafael Angarita
Shufan Jiang (CRESTIC, ISEP), Rafael Angarita (ISEP), Stephane Cormier (CRESTIC), Francis Rousseaux (CRESTIC)
Fine-tuning BERT-based models for Plant Health Bulletin Classification
null
Technology and Environment Workshop'21, Jan 2021, Montpellier, France
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the era of digitization, different actors in agriculture produce numerous data. Such data contains already latent historical knowledge in the domain. This knowledge enables us to precisely study natural hazards within global or local aspects, and then improve the risk prevention tasks and augment the yield, which ...
[ { "created": "Fri, 29 Jan 2021 08:14:35 GMT", "version": "v1" } ]
2021-02-02
[ [ "Jiang", "Shufan", "", "CRESTIC, ISEP" ], [ "Angarita", "Rafael", "", "ISEP" ], [ "Cormier", "Stephane", "", "CRESTIC" ], [ "Rousseaux", "Francis", "", "CRESTIC" ] ]
2102.00841
Alexander Sagel
Alexander Sagel, Julian W\"ormann, Hao Shen
Dynamic Texture Recognition via Nuclear Distances on Kernelized Scattering Histogram Spaces
\c{opyright} 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to se...
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
10.1109/ICASSP39728.2021.9414783
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Distance-based dynamic texture recognition is an important research field in multimedia processing with applications ranging from retrieval to segmentation of video data. Based on the conjecture that the most distinctive characteristic of a dynamic texture is the appearance of its individual frames, this work propose...
[ { "created": "Mon, 1 Feb 2021 13:54:24 GMT", "version": "v1" } ]
2021-05-17
[ [ "Sagel", "Alexander", "" ], [ "Wörmann", "Julian", "" ], [ "Shen", "Hao", "" ] ]
2102.00881
G\"ul\c{s}en Eryi\u{g}it
G\"ul\c{s}en Eryi\u{g}it, Ali \c{S}enta\c{s}, Johanna Monti
Gamified Crowdsourcing for Idiom Corpora Construction
25 pages, 8 figures, 6 tables
Natural Language Engineering, Cambridge Press, 2022
10.1017/S1351324921000401
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Learning idiomatic expressions is seen as one of the most challenging stages in second language learning because of their unpredictable meaning. A similar situation holds for their identification within natural language processing applications such as machine translation and parsing. The lack of high-quality usage sa...
[ { "created": "Mon, 1 Feb 2021 14:44:43 GMT", "version": "v1" } ]
2022-01-21
[ [ "Eryiğit", "Gülşen", "" ], [ "Şentaş", "Ali", "" ], [ "Monti", "Johanna", "" ] ]
2102.00898
Mohit Sewak
Mohit Sewak and Sanjay K. Sahay and Hemant Rathore
DRLDO: A novel DRL based De-ObfuscationSystem for Defense against Metamorphic Malware
null
Defence Science Journal, 71(1), 55-65
10.14429/dsj.71.15780
null
cs.CR cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a novel mechanism to normalize metamorphic and obfuscated malware down at the opcode level and hence create an advanced metamorphic malware de-obfuscation and defense system. We name this system DRLDO, for Deep Reinforcement Learning based De-Obfuscator. With the inclusion of the DRLDO as a ...
[ { "created": "Mon, 1 Feb 2021 15:16:18 GMT", "version": "v1" } ]
2021-02-02
[ [ "Sewak", "Mohit", "" ], [ "Sahay", "Sanjay K.", "" ], [ "Rathore", "Hemant", "" ] ]
2102.00997
Gorka Azkune
Aitzol Elu, Gorka Azkune, Oier Lopez de Lacalle, Ignacio Arganda-Carreras, Aitor Soroa, Eneko Agirre
Inferring spatial relations from textual descriptions of images
Accepted in Pattern Recognition
Pattern Recognition, Volume 113, 2021, 107847
10.1016/j.patcog.2021.107847
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generating an image from its textual description requires both a certain level of language understanding and common sense knowledge about the spatial relations of the physical entities being described. In this work, we focus on inferring the spatial relation between entities, a key step in the process of composing sc...
[ { "created": "Mon, 1 Feb 2021 17:21:13 GMT", "version": "v1" } ]
2021-02-03
[ [ "Elu", "Aitzol", "" ], [ "Azkune", "Gorka", "" ], [ "de Lacalle", "Oier Lopez", "" ], [ "Arganda-Carreras", "Ignacio", "" ], [ "Soroa", "Aitor", "" ], [ "Agirre", "Eneko", "" ] ]
2102.01013
Valentin Pelloin
Valentin Pelloin, Nathalie Camelin, Antoine Laurent, Renato De Mori, Antoine Caubri\`ere, Yannick Est\`eve, Sylvain Meignier
End2End Acoustic to Semantic Transduction
Accepted at IEEE ICASSP 2021
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
10.1109/ICASSP39728.2021.9413581
null
cs.CL cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a novel end-to-end sequence-to-sequence spoken language understanding model using an attention mechanism. It reliably selects contextual acoustic features in order to hypothesize semantic contents. An initial architecture capable of extracting all pronounced words and concepts from acoustic ...
[ { "created": "Mon, 1 Feb 2021 17:42:59 GMT", "version": "v1" } ]
2021-05-20
[ [ "Pelloin", "Valentin", "" ], [ "Camelin", "Nathalie", "" ], [ "Laurent", "Antoine", "" ], [ "De Mori", "Renato", "" ], [ "Caubrière", "Antoine", "" ], [ "Estève", "Yannick", "" ], [ "Meignier", "Sylvain", "...
2102.01149
Devorah Kletenik
Lisa Hellerstein, Devorah Kletenik and Srinivasan Parthasarathy
A Tight Bound for Stochastic Submodular Cover
This work extends the result of Srinivasan Parthasarathy in his paper arXiv:1803.07639 from the problem of Stochastic Set Cover to that of Stochastic Submodular Cover
Journal of Artificial Intelligence Research 71(2021) 347 - 370
10.1613/jair.1.12368
null
cs.DS cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
We show that the Adaptive Greedy algorithm of Golovin and Krause (2011) achieves an approximation bound of $(\ln (Q/\eta)+1)$ for Stochastic Submodular Cover: here $Q$ is the "goal value" and $\eta$ is the smallest non-zero marginal increase in utility deliverable by an item. (For integer-valued utility functions, we...
[ { "created": "Mon, 1 Feb 2021 20:37:40 GMT", "version": "v1" }, { "created": "Mon, 2 Aug 2021 04:26:17 GMT", "version": "v2" } ]
2021-08-03
[ [ "Hellerstein", "Lisa", "" ], [ "Kletenik", "Devorah", "" ], [ "Parthasarathy", "Srinivasan", "" ] ]
2102.01260
Xiong Liu
Xiong Liu, Craig E. Thomas, Christian C. Felder
The impact of external innovation on new drug approvals: A retrospective analysis
null
International Journal of Pharmaceutics, Volume 563, Pages 273-281, 2019
10.1016/j.ijpharm.2018.12.093
PMID: 30664998
cs.CL cs.CY q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pharmaceutical companies are relying more often on external sources of innovation to boost their discovery research productivity. However, more in-depth knowledge about how external innovation may translate to successful product launches is still required in order to better understand how to best leverage the innovat...
[ { "created": "Tue, 2 Feb 2021 02:21:34 GMT", "version": "v1" } ]
2021-02-03
[ [ "Liu", "Xiong", "" ], [ "Thomas", "Craig E.", "" ], [ "Felder", "Christian C.", "" ] ]
2102.01284
Peng Yao
Peng Yao, Shuwei Shen, Mengjuan Xu, Peng Liu, Fan Zhang, Jinyu Xing, Pengfei Shao, Benjamin Kaffenberger, and Ronald X. Xu
Single Model Deep Learning on Imbalanced Small Datasets for Skin Lesion Classification
null
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2021
10.1109/TMI.2021.3136682
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep convolutional neural network (DCNN) models have been widely explored for skin disease diagnosis and some of them have achieved the diagnostic outcomes comparable or even superior to those of dermatologists. However, broad implementation of DCNN in skin disease detection is hindered by small size and data imbalan...
[ { "created": "Tue, 2 Feb 2021 03:48:55 GMT", "version": "v1" }, { "created": "Fri, 11 Feb 2022 08:40:10 GMT", "version": "v2" } ]
2022-02-14
[ [ "Yao", "Peng", "" ], [ "Shen", "Shuwei", "" ], [ "Xu", "Mengjuan", "" ], [ "Liu", "Peng", "" ], [ "Zhang", "Fan", "" ], [ "Xing", "Jinyu", "" ], [ "Shao", "Pengfei", "" ], [ "Kaffenberger", "Ben...
2102.01295
Heecheol Kim
Heecheol Kim, Yoshiyuki Ohmura, and Yasuo Kuniyoshi
Gaze-based dual resolution deep imitation learning for high-precision dexterous robot manipulation
8 pages. The supplementary video can be found at: https://www.youtube.com/watch?v=ytpChcFqD5g Published in IEEE Robotics and Automation Letters. Replaced to add video url in the manuscript
IEEE Robotics and Automation Letters, Vol. 6, No. 2, 2021
10.1109/LRA.2021.3059619
null
cs.RO cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
A high-precision manipulation task, such as needle threading, is challenging. Physiological studies have proposed connecting low-resolution peripheral vision and fast movement to transport the hand into the vicinity of an object, and using high-resolution foveated vision to achieve the accurate homing of the hand to ...
[ { "created": "Tue, 2 Feb 2021 04:11:09 GMT", "version": "v1" }, { "created": "Wed, 3 Mar 2021 03:50:20 GMT", "version": "v2" }, { "created": "Mon, 26 Feb 2024 10:09:46 GMT", "version": "v3" } ]
2024-02-27
[ [ "Kim", "Heecheol", "" ], [ "Ohmura", "Yoshiyuki", "" ], [ "Kuniyoshi", "Yasuo", "" ] ]
2102.01301
Yi-Jun Cao
Yi-Jun Cao, Chuan Lin, and Yong-Jie Li
Learning Crisp Boundaries Using Deep Refinement Network and Adaptive Weighting Loss
11 pages, 7 figures
IEEE Transactions on Multimedia, vol. 23, pp. 761-771, 2021
10.1109/TED.2020.3041567
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Significant progress has been made in boundary detection with the help of convolutional neural networks. Recent boundary detection models not only focus on real object boundary detection but also "crisp" boundaries (precisely localized along the object's contour). There are two methods to evaluate crisp boundary perf...
[ { "created": "Tue, 2 Feb 2021 04:22:35 GMT", "version": "v1" }, { "created": "Wed, 3 Mar 2021 07:15:10 GMT", "version": "v2" } ]
2021-03-10
[ [ "Cao", "Yi-Jun", "" ], [ "Lin", "Chuan", "" ], [ "Li", "Yong-Jie", "" ] ]
2102.01380
Zhong Meng
Zhong Meng, Naoyuki Kanda, Yashesh Gaur, Sarangarajan Parthasarathy, Eric Sun, Liang Lu, Xie Chen, Jinyu Li, Yifan Gong
Internal Language Model Training for Domain-Adaptive End-to-End Speech Recognition
5 pages, ICASSP 2021
2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Toronto, Canada
null
null
eess.AS cs.AI cs.CL cs.LG cs.SD
http://creativecommons.org/licenses/by/4.0/
The efficacy of external language model (LM) integration with existing end-to-end (E2E) automatic speech recognition (ASR) systems can be improved significantly using the internal language model estimation (ILME) method. In this method, the internal LM score is subtracted from the score obtained by interpolating the ...
[ { "created": "Tue, 2 Feb 2021 08:15:02 GMT", "version": "v1" }, { "created": "Thu, 22 Apr 2021 19:16:04 GMT", "version": "v2" } ]
2021-04-26
[ [ "Meng", "Zhong", "" ], [ "Kanda", "Naoyuki", "" ], [ "Gaur", "Yashesh", "" ], [ "Parthasarathy", "Sarangarajan", "" ], [ "Sun", "Eric", "" ], [ "Lu", "Liang", "" ], [ "Chen", "Xie", "" ], [ "Li", ...
2102.01405
Ruben Tolosana
Ruben Tolosana, Juan Carlos Ruiz-Garcia, Ruben Vera-Rodriguez, Jaime Herreros-Rodriguez, Sergio Romero-Tapiador, Aythami Morales, Julian Fierrez
Child-Computer Interaction with Mobile Devices: Recent Works, New Dataset, and Age Detection
null
IEEE Transactions on Emerging Topics in Computing, 2022
10.1109/TETC.2022.3150836
null
cs.HC cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
This article provides an overview of recent research in Child-Computer Interaction with mobile devices and describe our framework ChildCI intended for: i) overcoming the lack of large-scale publicly available databases in the area, ii) generating a better understanding of the cognitive and neuromotor development of c...
[ { "created": "Tue, 2 Feb 2021 09:51:58 GMT", "version": "v1" }, { "created": "Mon, 21 Feb 2022 08:57:57 GMT", "version": "v2" }, { "created": "Tue, 22 Feb 2022 08:38:02 GMT", "version": "v3" } ]
2022-02-23
[ [ "Tolosana", "Ruben", "" ], [ "Ruiz-Garcia", "Juan Carlos", "" ], [ "Vera-Rodriguez", "Ruben", "" ], [ "Herreros-Rodriguez", "Jaime", "" ], [ "Romero-Tapiador", "Sergio", "" ], [ "Morales", "Aythami", "" ], [ "Fierr...
2102.01460
Alberto Pretto
Alessandro Saviolo, Matteo Bonotto, Daniele Evangelista, Marco Imperoli, Jacopo Lazzaro, Emanuele Menegatti and Alberto Pretto
Learning to Segment Human Body Parts with Synthetically Trained Deep Convolutional Networks
This paper has been published in: Proceedings of the 16th International Conference on Intelligent Autonomous Systems (IAS 2021)
Proceedings of the 16th International Conference on Intelligent Autonomous Systems (IAS 2021)
10.1007/978-3-030-95892-3_52
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a new framework for human body part segmentation based on Deep Convolutional Neural Networks trained using only synthetic data. The proposed approach achieves cutting-edge results without the need of training the models with real annotated data of human body parts. Our contributions include a data...
[ { "created": "Tue, 2 Feb 2021 12:26:50 GMT", "version": "v1" }, { "created": "Tue, 9 Nov 2021 15:06:02 GMT", "version": "v2" }, { "created": "Tue, 7 Jun 2022 15:10:20 GMT", "version": "v3" } ]
2022-06-08
[ [ "Saviolo", "Alessandro", "" ], [ "Bonotto", "Matteo", "" ], [ "Evangelista", "Daniele", "" ], [ "Imperoli", "Marco", "" ], [ "Lazzaro", "Jacopo", "" ], [ "Menegatti", "Emanuele", "" ], [ "Pretto", "Alberto", ...
2102.01486
Cheng Ma
Cheng Ma, Jiwen Lu, Jie Zhou
Rank-Consistency Deep Hashing for Scalable Multi-Label Image Search
null
IEEE Transactions on Multimedia, 2020
10.1109/TMM.2020.3034534
null
cs.CV cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As hashing becomes an increasingly appealing technique for large-scale image retrieval, multi-label hashing is also attracting more attention for the ability to exploit multi-level semantic contents. In this paper, we propose a novel deep hashing method for scalable multi-label image search. Unlike existing approache...
[ { "created": "Tue, 2 Feb 2021 13:46:58 GMT", "version": "v1" } ]
2021-02-03
[ [ "Ma", "Cheng", "" ], [ "Lu", "Jiwen", "" ], [ "Zhou", "Jie", "" ] ]
2102.01498
Iuliana Marin
Andrei Vasilateanu, Nicolae Goga, Elena-Alice Tanase, Iuliana Marin
Enterprise domain ontology learning from web-based corpus
null
2015 6th International Conference on Computing, Communication and Networking Technologies (ICCCNT)
10.1109/ICCCNT.2015.7395227
null
cs.AI cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Enterprise knowledge is a key asset in the competing and fast-changing corporate landscape. The ability to learn, store and distribute implicit and explicit knowledge can be the difference between success and failure. While enterprise knowledge management is a well-defined research domain, current implementations lac...
[ { "created": "Fri, 29 Jan 2021 17:08:29 GMT", "version": "v1" } ]
2021-02-16
[ [ "Vasilateanu", "Andrei", "" ], [ "Goga", "Nicolae", "" ], [ "Tanase", "Elena-Alice", "" ], [ "Marin", "Iuliana", "" ] ]
2102.01502
Satyapriya Krishna
Satyapriya Krishna, Rahul Gupta, Christophe Dupuy
ADePT: Auto-encoder based Differentially Private Text Transformation
null
The 16th conference of the European Chapter of the Association for Computational Linguistics (EACL), 2021
null
null
cs.CR cs.AI cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
Privacy is an important concern when building statistical models on data containing personal information. Differential privacy offers a strong definition of privacy and can be used to solve several privacy concerns (Dwork et al., 2014). Multiple solutions have been proposed for the differentially-private transformati...
[ { "created": "Fri, 29 Jan 2021 23:15:24 GMT", "version": "v1" } ]
2021-02-03
[ [ "Krishna", "Satyapriya", "" ], [ "Gupta", "Rahul", "" ], [ "Dupuy", "Christophe", "" ] ]
2102.01565
Juan Pedro Dominguez-Morales
Luis J. Mu\~noz-Molina, Ignacio Cazorla-Pi\~nar, Juan P. Dominguez-Morales, Fernando Perez-Pe\~na
Real-time detection of uncalibrated sensors using Neural Networks
null
Neural Comput & Applic (2022)
10.1007/s00521-021-06865-z
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Nowadays, sensors play a major role in several contexts like science, industry and daily life which benefit of their use. However, the retrieved information must be reliable. Anomalies in the behavior of sensors can give rise to critical consequences such as ruining a scientific project or jeopardizing the quality of...
[ { "created": "Tue, 2 Feb 2021 15:44:39 GMT", "version": "v1" } ]
2022-01-26
[ [ "Muñoz-Molina", "Luis J.", "" ], [ "Cazorla-Piñar", "Ignacio", "" ], [ "Dominguez-Morales", "Juan P.", "" ], [ "Perez-Peña", "Fernando", "" ] ]
2102.01578
Marco Gaido
Marco Gaido, Mauro Cettolo, Matteo Negri, Marco Turchi
CTC-based Compression for Direct Speech Translation
Accepted at EACL2021
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (2021), 690-696
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
Previous studies demonstrated that a dynamic phone-informed compression of the input audio is beneficial for speech translation (ST). However, they required a dedicated model for phone recognition and did not test this solution for direct ST, in which a single model translates the input audio into the target language...
[ { "created": "Tue, 2 Feb 2021 16:09:19 GMT", "version": "v1" } ]
2021-10-15
[ [ "Gaido", "Marco", "" ], [ "Cettolo", "Mauro", "" ], [ "Negri", "Matteo", "" ], [ "Turchi", "Marco", "" ] ]
2102.01579
Xiangyu Xu
Xiangyu Xu, Yongrui Ma, Wenxiu Sun, Ming-Hsuan Yang
Exploiting Raw Images for Real-Scene Super-Resolution
A larger version with higher-resolution figures is available at: https://sites.google.com/view/xiangyuxu. arXiv admin note: text overlap with arXiv:1905.12156
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Super-resolution is a fundamental problem in computer vision which aims to overcome the spatial limitation of camera sensors. While significant progress has been made in single image super-resolution, most algorithms only perform well on synthetic data, which limits their applications in real scenarios. In this paper...
[ { "created": "Tue, 2 Feb 2021 16:10:15 GMT", "version": "v1" } ]
2021-02-03
[ [ "Xu", "Xiangyu", "" ], [ "Ma", "Yongrui", "" ], [ "Sun", "Wenxiu", "" ], [ "Yang", "Ming-Hsuan", "" ] ]
2102.01582
Mats Richter
Mats L. Richter, Wolf Byttner, Ulf Krumnack, Ludwdig Schallner, Justin Shenk
Size Matters
Preprint
Artificial Neural Networks and Machine Learning ICANN 2021 133-144
10.1007/978-3-030-86340-1_11
null
cs.LG cs.AI cs.CV
http://creativecommons.org/licenses/by/4.0/
Fully convolutional neural networks can process input of arbitrary size by applying a combination of downsampling and pooling. However, we find that fully convolutional image classifiers are not agnostic to the input size but rather show significant differences in performance: presenting the same image at different s...
[ { "created": "Tue, 2 Feb 2021 16:17:52 GMT", "version": "v1" }, { "created": "Tue, 9 Feb 2021 09:00:14 GMT", "version": "v2" } ]
2021-10-13
[ [ "Richter", "Mats L.", "" ], [ "Byttner", "Wolf", "" ], [ "Krumnack", "Ulf", "" ], [ "Schallner", "Ludwdig", "" ], [ "Shenk", "Justin", "" ] ]
2102.01645
Federico Galatolo
Federico A. Galatolo and Mario G.C.A. Cimino and Gigliola Vaglini
Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search
null
IMPROVE, ISBN 978-989-758-511-1, pages 166-174 (2021)
10.5220/0010503701660174
null
cs.NE cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this research work we present CLIP-GLaSS, a novel zero-shot framework to generate an image (or a caption) corresponding to a given caption (or image). CLIP-GLaSS is based on the CLIP neural network, which, given an image and a descriptive caption, provides similar embeddings. Differently, CLIP-GLaSS takes a captio...
[ { "created": "Tue, 2 Feb 2021 18:00:13 GMT", "version": "v1" }, { "created": "Wed, 3 Feb 2021 12:14:49 GMT", "version": "v2" }, { "created": "Fri, 26 Feb 2021 22:42:49 GMT", "version": "v3" }, { "created": "Fri, 1 Oct 2021 15:45:51 GMT", "version": "v4" } ]
2021-10-04
[ [ "Galatolo", "Federico A.", "" ], [ "Cimino", "Mario G. C. A.", "" ], [ "Vaglini", "Gigliola", "" ] ]
2102.01767
Jorge Miguel Ferreira Da Silva
Jorge Miguel Silva, Diogo Pratas, Rui Antunes, S\'ergio Matos, and Armando J. Pinho
Automatic analysis of artistic paintings using information-based measures
Website: http://panther.web.ua.pt 24 Pages; 19 pages article; 5 pages supplementary material
Pattern Recognition (2021) 107864
10.1016/j.patcog.2021.107864
null
cs.CV cs.IT cs.LG math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The artistic community is increasingly relying on automatic computational analysis for authentication and classification of artistic paintings. In this paper, we identify hidden patterns and relationships present in artistic paintings by analysing their complexity, a measure that quantifies the sum of characteristics...
[ { "created": "Tue, 2 Feb 2021 21:40:30 GMT", "version": "v1" } ]
2021-02-10
[ [ "Silva", "Jorge Miguel", "" ], [ "Pratas", "Diogo", "" ], [ "Antunes", "Rui", "" ], [ "Matos", "Sérgio", "" ], [ "Pinho", "Armando J.", "" ] ]
2102.01780
Daniel Severin Dr.
Mauro Lucci, Daniel Sever\'in, Paula Zabala
A metaheuristic for crew scheduling in a pickup-and-delivery problem with time windows
null
Intl. Trans. in Op. Res., vol. 30, 2023, pp. 970-1001
10.1111/itor.13096
null
cs.AI cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A vehicle routing and crew scheduling problem (VRCSP) consists of simultaneously planning the routes of a fleet of vehicles and scheduling the crews, where the vehicle-crew correspondence is not fixed through time. This allows a greater planning flexibility and a more efficient use of the fleet, but in counterpart, a...
[ { "created": "Tue, 2 Feb 2021 22:14:10 GMT", "version": "v1" } ]
2024-07-11
[ [ "Lucci", "Mauro", "" ], [ "Severín", "Daniel", "" ], [ "Zabala", "Paula", "" ] ]
2102.01826
Zhewei Sun
Zhewei Sun, Richard Zemel, Yang Xu
A Computational Framework for Slang Generation
Accepted for publication in TACL 2021. Author's final version
Transactions of the Association for Computational Linguistics 2021; 9 462-478
10.1162/tacl_a_00378
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Slang is a common type of informal language, but its flexible nature and paucity of data resources present challenges for existing natural language systems. We take an initial step toward machine generation of slang by developing a framework that models the speaker's word choice in slang context. Our framework encode...
[ { "created": "Wed, 3 Feb 2021 01:19:07 GMT", "version": "v1" }, { "created": "Sat, 22 May 2021 04:46:48 GMT", "version": "v2" } ]
2021-05-25
[ [ "Sun", "Zhewei", "" ], [ "Zemel", "Richard", "" ], [ "Xu", "Yang", "" ] ]
2102.01850
Ru Li
Ru Li, Chuan Wang, Jue Wang, Guanghui Liu, Heng-Yu Zhang, Bing Zeng, Shuaicheng Liu
UPHDR-GAN: Generative Adversarial Network for High Dynamic Range Imaging with Unpaired Data
Accepted by IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
IEEE Transactions on Circuits and Systems for Video Technology, 2022
10.1109/TCSVT.2022.3190057
null
eess.IV cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The paper proposes a method to effectively fuse multi-exposure inputs and generate high-quality high dynamic range (HDR) images with unpaired datasets. Deep learning-based HDR image generation methods rely heavily on paired datasets. The ground truth images play a leading role in generating reasonable HDR images. Dat...
[ { "created": "Wed, 3 Feb 2021 03:09:14 GMT", "version": "v1" }, { "created": "Fri, 15 Jul 2022 07:54:33 GMT", "version": "v2" } ]
2022-07-18
[ [ "Li", "Ru", "" ], [ "Wang", "Chuan", "" ], [ "Wang", "Jue", "" ], [ "Liu", "Guanghui", "" ], [ "Zhang", "Heng-Yu", "" ], [ "Zeng", "Bing", "" ], [ "Liu", "Shuaicheng", "" ] ]
2102.01906
Vinod Kumar Kurmi
Vinod K Kurmi, Badri N. Patro, Venkatesh K. Subramanian, Vinay P. Namboodiri
Do Not Forget to Attend to Uncertainty while Mitigating Catastrophic Forgetting
Accepted WACV 2021
WACV 2021
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
One of the major limitations of deep learning models is that they face catastrophic forgetting in an incremental learning scenario. There have been several approaches proposed to tackle the problem of incremental learning. Most of these methods are based on knowledge distillation and do not adequately utilize the inf...
[ { "created": "Wed, 3 Feb 2021 06:54:52 GMT", "version": "v1" } ]
2021-02-04
[ [ "Kurmi", "Vinod K", "" ], [ "Patro", "Badri N.", "" ], [ "Subramanian", "Venkatesh K.", "" ], [ "Namboodiri", "Vinay P.", "" ] ]
2102.01968
Claire Theobald
Claire Theobald (LORIA), Fr\'ed\'eric Pennerath (LORIA), Brieuc Conan-Guez (LORIA), Miguel Couceiro (LORIA), Amedeo Napoli (LORIA)
A Bayesian Neural Network based on Dropout Regulation
null
Workshop on Uncertainty in Machine Learning (WUML) at ECML-PKDD 2020 Conference, Eyke H{\"u}llermeier; S{\'e}bastien Destercke, 2020, N.A. (online), France
null
null
cs.LG cs.AI cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bayesian Neural Networks (BNN) have recently emerged in the Deep Learning world for dealing with uncertainty estimation in classification tasks, and are used in many application domains such as astrophysics, autonomous driving...BNN assume a prior over the weights of a neural network instead of point estimates, enabl...
[ { "created": "Wed, 3 Feb 2021 09:39:50 GMT", "version": "v1" } ]
2021-02-04
[ [ "Theobald", "Claire", "", "LORIA" ], [ "Pennerath", "Frédéric", "", "LORIA" ], [ "Conan-Guez", "Brieuc", "", "LORIA" ], [ "Couceiro", "Miguel", "", "LORIA" ], [ "Napoli", "Amedeo", "", "LORIA" ] ]
2102.02189
Young-Suk Lee Dr.
Janaki Sheth and Young-Suk Lee and Ramon Fernandez Astudillo and Tahira Naseem and Radu Florian and Salim Roukos and Todd Ward
Bootstrapping Multilingual AMR with Contextual Word Alignments
null
EACL 2021
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
We develop high performance multilingualAbstract Meaning Representation (AMR) sys-tems by projecting English AMR annotationsto other languages with weak supervision. Weachieve this goal by bootstrapping transformer-based multilingual word embeddings, in partic-ular those from cross-lingual RoBERTa (XLM-R large). We d...
[ { "created": "Wed, 3 Feb 2021 18:35:55 GMT", "version": "v1" } ]
2022-05-09
[ [ "Sheth", "Janaki", "" ], [ "Lee", "Young-Suk", "" ], [ "Astudillo", "Ramon Fernandez", "" ], [ "Naseem", "Tahira", "" ], [ "Florian", "Radu", "" ], [ "Roukos", "Salim", "" ], [ "Ward", "Todd", "" ] ]
2102.02304
Panayiotis Danassis
Panayiotis Danassis, Zeki Doruk Erden, Boi Faltings
Improved Cooperation by Exploiting a Common Signal
Accepted to the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021)
An extended version of this paper has been published in the Autonomous Agents and Multi-Agent Systems (2022)
10.1007/s10458-021-09541-7
null
cs.MA cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Can artificial agents benefit from human conventions? Human societies manage to successfully self-organize and resolve the tragedy of the commons in common-pool resources, in spite of the bleak prediction of non-cooperative game theory. On top of that, real-world problems are inherently large-scale and of low observa...
[ { "created": "Wed, 3 Feb 2021 21:27:53 GMT", "version": "v1" } ]
2022-03-29
[ [ "Danassis", "Panayiotis", "" ], [ "Erden", "Zeki Doruk", "" ], [ "Faltings", "Boi", "" ] ]
2102.02585
V\'it Novotn\'y
V\'it Novotn\'y (1) and Eniafe Festus Ayetiran (1) and Dalibor Ba\v{c}ovsk\'y (1) and D\'avid Lupt\'ak (1) and Michal \v{S}tef\'anik (1) and Petr Sojka (1) ((1) Faculty of Informatics Masaryk University)
One Size Does Not Fit All: Finding the Optimal Subword Sizes for FastText Models across Languages
null
RANLP (2021) 1072-1078
10.26615/978-954-452-072-4_121
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Unsupervised representation learning of words from large multilingual corpora is useful for downstream tasks such as word sense disambiguation, semantic text similarity, and information retrieval. The representation precision of log-bilinear fastText models is mostly due to their use of subword information. In previo...
[ { "created": "Thu, 4 Feb 2021 12:59:36 GMT", "version": "v1" }, { "created": "Sat, 21 Aug 2021 12:13:23 GMT", "version": "v2" }, { "created": "Mon, 20 Sep 2021 17:50:51 GMT", "version": "v3" } ]
2021-09-21
[ [ "Novotný", "Vít", "", "Faculty of Informatics Masaryk University" ], [ "Ayetiran", "Eniafe Festus", "", "Faculty of Informatics Masaryk University" ], [ "Bačovský", "Dalibor", "", "Faculty of Informatics Masaryk University" ], [ "Lupták", "Dávid"...
2102.02636
Hendri Murfi
Hendri Murfi, Natasha Rosaline, Nora Hariadi
Deep Autoencoder-based Fuzzy C-Means for Topic Detection
18 pages
Array 13 (2022)
10.1016/j.array.2021.100124
null
cs.IR cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
Topic detection is a process for determining topics from a collection of textual data. One of the topic detection methods is a clustering-based method, which assumes that the centroids are topics. The clustering method has the advantage that it can process data with negative representations. Therefore, the clustering...
[ { "created": "Tue, 2 Feb 2021 07:41:52 GMT", "version": "v1" } ]
2021-12-28
[ [ "Murfi", "Hendri", "" ], [ "Rosaline", "Natasha", "" ], [ "Hariadi", "Nora", "" ] ]
2102.02711
Soumick Chatterjee
Chompunuch Sarasaen, Soumick Chatterjee, Mario Breitkopf, Georg Rose, Andreas N\"urnberger and Oliver Speck
Fine-tuning deep learning model parameters for improved super-resolution of dynamic MRI with prior-knowledge
null
Artificial Intelligence in Medicine (2021) 102196
10.1016/j.artmed.2021.102196
null
eess.IV cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Dynamic imaging is a beneficial tool for interventions to assess physiological changes. Nonetheless during dynamic MRI, while achieving a high temporal resolution, the spatial resolution is compromised. To overcome this spatio-temporal trade-off, this research presents a super-resolution (SR) MRI reconstruction with ...
[ { "created": "Thu, 4 Feb 2021 16:11:53 GMT", "version": "v1" }, { "created": "Fri, 23 Apr 2021 12:24:51 GMT", "version": "v2" }, { "created": "Sat, 4 Sep 2021 21:25:18 GMT", "version": "v3" }, { "created": "Sat, 23 Oct 2021 10:42:29 GMT", "version": "v4" } ]
2021-10-26
[ [ "Sarasaen", "Chompunuch", "" ], [ "Chatterjee", "Soumick", "" ], [ "Breitkopf", "Mario", "" ], [ "Rose", "Georg", "" ], [ "Nürnberger", "Andreas", "" ], [ "Speck", "Oliver", "" ] ]
2102.02771
Jun Wang
Jun Wang, Xiaohan Yu, Yongsheng Gao
Mask Guided Attention For Fine-Grained Patchy Image Classification
Accepted to ICIP2021
2021 IEEE International Conference on Image Processing (ICIP), 2021, pp. 1044-1048
10.1109/ICIP42928.2021.9506424
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we present a novel mask guided attention (MGA) method for fine-grained patchy image classification. The key challenge of fine-grained patchy image classification lies in two folds, ultra-fine-grained inter-category variances among objects and very few data available for training. This motivates us to co...
[ { "created": "Thu, 4 Feb 2021 17:54:50 GMT", "version": "v1" }, { "created": "Wed, 22 Sep 2021 10:09:32 GMT", "version": "v2" } ]
2021-09-23
[ [ "Wang", "Jun", "" ], [ "Yu", "Xiaohan", "" ], [ "Gao", "Yongsheng", "" ] ]
2102.02789
Vivien Cabannes
Vivien Cabannes, Francis Bach, Alessandro Rudi
Disambiguation of weak supervision with exponential convergence rates
22 pages; 6 figures
Proceedings of the 38th International Conference on Machine Learning, PMLR 139, 2021
null
null
cs.LG cs.AI stat.ML
http://creativecommons.org/licenses/by/4.0/
Machine learning approached through supervised learning requires expensive annotation of data. This motivates weakly supervised learning, where data are annotated with incomplete yet discriminative information. In this paper, we focus on partial labelling, an instance of weak supervision where, from a given input, we...
[ { "created": "Thu, 4 Feb 2021 18:14:32 GMT", "version": "v1" }, { "created": "Wed, 26 May 2021 16:14:29 GMT", "version": "v2" }, { "created": "Thu, 15 Jul 2021 14:29:24 GMT", "version": "v3" } ]
2021-07-16
[ [ "Cabannes", "Vivien", "" ], [ "Bach", "Francis", "" ], [ "Rudi", "Alessandro", "" ] ]
2102.02887
Shiwei Liu
Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy
Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training
16 pages; 10 figures; Published in Proceedings of the 38th International Conference on Machine Learning. Code can be found https://github.com/Shiweiliuiiiiiii/In-Time-Over-Parameterization
Proceedings of the 38th International Conference on Machine Learning (2021)
null
null
cs.LG cs.AI cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we introduce a new perspective on training deep neural networks capable of state-of-the-art performance without the need for the expensive over-parameterization by proposing the concept of In-Time Over-Parameterization (ITOP) in sparse training. By starting from a random sparse network and continuously...
[ { "created": "Thu, 4 Feb 2021 20:59:31 GMT", "version": "v1" }, { "created": "Sat, 13 Feb 2021 23:36:57 GMT", "version": "v2" }, { "created": "Tue, 15 Jun 2021 05:01:46 GMT", "version": "v3" } ]
2021-06-16
[ [ "Liu", "Shiwei", "" ], [ "Yin", "Lu", "" ], [ "Mocanu", "Decebal Constantin", "" ], [ "Pechenizkiy", "Mykola", "" ] ]
2102.02917
Allison Lahnala
Allison Lahnala, Gauri Kambhatla, Jiajun Peng, Matthew Whitehead, Gillian Minnehan, Eric Guldan, Jonathan K. Kummerfeld, An{\i}l \c{C}amc{\i}, Rada Mihalcea
Chord Embeddings: Analyzing What They Capture and Their Role for Next Chord Prediction and Artist Attribute Prediction
16 pages, accepted to EvoMUSART
Computational Intelligence in Music, Sound, Art and Design, 10th International Conference, EvoMUSART 2021
null
null
cs.SD cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Natural language processing methods have been applied in a variety of music studies, drawing the connection between music and language. In this paper, we expand those approaches by investigating \textit{chord embeddings}, which we apply in two case studies to address two key questions: (1) what musical information do...
[ { "created": "Thu, 4 Feb 2021 22:17:17 GMT", "version": "v1" } ]
2021-02-08
[ [ "Lahnala", "Allison", "" ], [ "Kambhatla", "Gauri", "" ], [ "Peng", "Jiajun", "" ], [ "Whitehead", "Matthew", "" ], [ "Minnehan", "Gillian", "" ], [ "Guldan", "Eric", "" ], [ "Kummerfeld", "Jonathan K.", ""...
2102.03022
Tim Miller
Zhengshang Liu, Yue Yang, Tim Miller, and Peta Masters
Deceptive Reinforcement Learning for Privacy-Preserving Planning
null
Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021)
null
null
cs.LG cs.AI cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we study the problem of deceptive reinforcement learning to preserve the privacy of a reward function. Reinforcement learning is the problem of finding a behaviour policy based on rewards received from exploratory behaviour. A key ingredient in reinforcement learning is a reward function, which determi...
[ { "created": "Fri, 5 Feb 2021 06:50:04 GMT", "version": "v1" } ]
2021-02-08
[ [ "Liu", "Zhengshang", "" ], [ "Yang", "Yue", "" ], [ "Miller", "Tim", "" ], [ "Masters", "Peta", "" ] ]
2102.03049
Shang Ran Huang
Fu-Shun Hsu, Shang-Ran Huang, Chien-Wen Huang, Chao-Jung Huang, Yuan-Ren Cheng, Chun-Chieh Chen, Jack Hsiao, Chung-Wei Chen, Li-Chin Chen, Yen-Chun Lai, Bi-Fang Hsu, Nian-Jhen Lin, Wan-Lin Tsai, Yi-Lin Wu, Tzu-Ling Tseng, Ching-Ting Tseng, Yi-Tsun Chen, Feipei Lai
Benchmarking of eight recurrent neural network variants for breath phase and adventitious sound detection on a self-developed open-access lung sound database-HF_Lung_V1
48 pages, 8 figures. Accepted by PLoS One
PLoS ONE, 2021, 16(7): e0254134
10.1371/journal.pone.0254134
null
cs.SD cs.AI cs.LG eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A reliable, remote, and continuous real-time respiratory sound monitor with automated respiratory sound analysis ability is urgently required in many clinical scenarios-such as in monitoring disease progression of coronavirus disease 2019-to replace conventional auscultation with a handheld stethoscope. However, a ro...
[ { "created": "Fri, 5 Feb 2021 08:21:28 GMT", "version": "v1" }, { "created": "Wed, 3 Mar 2021 15:22:55 GMT", "version": "v2" }, { "created": "Tue, 12 Jul 2022 09:04:06 GMT", "version": "v3" } ]
2022-07-13
[ [ "Hsu", "Fu-Shun", "" ], [ "Huang", "Shang-Ran", "" ], [ "Huang", "Chien-Wen", "" ], [ "Huang", "Chao-Jung", "" ], [ "Cheng", "Yuan-Ren", "" ], [ "Chen", "Chun-Chieh", "" ], [ "Hsiao", "Jack", "" ], [ ...
2102.03277
Llu\'is Alemany-Puig
Llu\'is Alemany-Puig, Juan Luis Esteban, Ramon Ferrer-i-Cancho
Minimum projective linearizations of trees in linear time
Here we have corrected a mistake we made in the previous version. In particular, line 7 of Algorithm 3.2 used to say: "For i = 1 to |C_v| ..."; it should be "For i = 2 to |C_v| ..." (notice the change from 'i=1' to 'i=2')
Information Processing Letters, 174:106204 (2022)
10.1016/j.ipl.2021.106204
null
cs.DS cs.CL cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Minimum Linear Arrangement problem (MLA) consists of finding a mapping $\pi$ from vertices of a graph to distinct integers that minimizes $\sum_{\{u,v\}\in E}|\pi(u) - \pi(v)|$. In that setting, vertices are often assumed to lie on a horizontal line and edges are drawn as semicircles above said line. For trees, v...
[ { "created": "Fri, 5 Feb 2021 16:35:38 GMT", "version": "v1" }, { "created": "Wed, 17 Feb 2021 14:20:33 GMT", "version": "v2" }, { "created": "Mon, 26 Jul 2021 14:02:41 GMT", "version": "v3" }, { "created": "Wed, 8 Sep 2021 15:19:02 GMT", "version": "v4" }, { "cre...
2024-09-13
[ [ "Alemany-Puig", "Lluís", "" ], [ "Esteban", "Juan Luis", "" ], [ "Ferrer-i-Cancho", "Ramon", "" ] ]
2102.03310
Michal Ciszewski
Micha{\l} Ciszewski, Jakob S\"ohl, Geurt Jongbloed
Improving state estimation through projection post-processing for activity recognition with application to football
This preprint has not undergone peer review (when applicable) or any post-submission improvements or corrections. The Version of Record of this article is published in Statistical Methods & Applications, and is available online at https://doi.org/10.1007/s10260-023-00696-z
Stat Methods Appl (2023)
10.1007/s10260-023-00696-z
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
The past decade has seen an increased interest in human activity recognition based on sensor data. Most often, the sensor data come unannotated, creating the need for fast labelling methods. For assessing the quality of the labelling, an appropriate performance measure has to be chosen. Our main contribution is a nov...
[ { "created": "Fri, 5 Feb 2021 17:32:39 GMT", "version": "v1" }, { "created": "Thu, 10 Jun 2021 09:43:01 GMT", "version": "v2" }, { "created": "Fri, 2 Sep 2022 10:27:28 GMT", "version": "v3" }, { "created": "Tue, 2 May 2023 19:56:30 GMT", "version": "v4" } ]
2023-05-04
[ [ "Ciszewski", "Michał", "" ], [ "Söhl", "Jakob", "" ], [ "Jongbloed", "Geurt", "" ] ]
2102.03380
Manuel L\'opez-Ib\'a\~nez
Manuel L\'opez-Ib\'a\~nez (University of M\'alaga, Spain), Juergen Branke (University of Warwick, UK), Lu\'is Paquete (University of Coimbra, Portugal)
Reproducibility in Evolutionary Computation
null
ACM Transactions on Evolutionary Learning and Optimization, 2021
10.1145/3466624
null
cs.AI cs.NE math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Experimental studies are prevalent in Evolutionary Computation (EC), and concerns about the reproducibility and replicability of such studies have increased in recent times, reflecting similar concerns in other scientific fields. In this article, we discuss, within the context of EC, the different types of reproducib...
[ { "created": "Fri, 5 Feb 2021 19:06:35 GMT", "version": "v1" }, { "created": "Tue, 29 Jun 2021 16:24:25 GMT", "version": "v2" } ]
2022-03-30
[ [ "López-Ibáñez", "Manuel", "", "University of Málaga, Spain" ], [ "Branke", "Juergen", "", "University of Warwick, UK" ], [ "Paquete", "Luís", "", "University of Coimbra,\n Portugal" ] ]
2102.03382
Tu Le
Tu Le, Danny Yuxing Huang, Noah Apthorpe, Yuan Tian
SkillBot: Identifying Risky Content for Children in Alexa Skills
null
ACM Transactions on Internet Technology, Volume 22, Issue 3, August 2022, Article 79, pp 1-31
10.1145/3539609
null
cs.MA cs.CL cs.CR cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many households include children who use voice personal assistants (VPA) such as Amazon Alexa. Children benefit from the rich functionalities of VPAs and third-party apps but are also exposed to new risks in the VPA ecosystem. In this paper, we first investigate "risky" child-directed voice apps that contain inapprop...
[ { "created": "Fri, 5 Feb 2021 19:07:39 GMT", "version": "v1" }, { "created": "Thu, 2 Jun 2022 02:28:15 GMT", "version": "v2" } ]
2022-10-13
[ [ "Le", "Tu", "" ], [ "Huang", "Danny Yuxing", "" ], [ "Apthorpe", "Noah", "" ], [ "Tian", "Yuan", "" ] ]
2102.03419
Dora Jambor
Dora Jambor, Komal Teru, Joelle Pineau, William L. Hamilton
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs
code available at https://github.com/dorajam/few-shot-link-prediction-paper
European Chapter of the ACL (EACL), 2021
null
null
cs.AI cs.CL cs.IR cs.LG cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Real-world knowledge graphs are often characterized by low-frequency relations - a challenge that has prompted an increasing interest in few-shot link prediction methods. These methods perform link prediction for a set of new relations, unseen during training, given only a few example facts of each relation at test t...
[ { "created": "Fri, 5 Feb 2021 21:04:31 GMT", "version": "v1" } ]
2021-02-09
[ [ "Jambor", "Dora", "" ], [ "Teru", "Komal", "" ], [ "Pineau", "Joelle", "" ], [ "Hamilton", "William L.", "" ] ]
2102.03444
Dominik Drees
Dominik Drees, Aaron Scherzinger, Ren\'e H\"agerling, Friedemann Kiefer, Xiaoyi Jiang
Scalable Robust Graph and Feature Extraction for Arbitrary Vessel Networks in Large Volumetric Datasets
null
BMC Bioinformatics 22 (2021) 346
10.1186/s12859-021-04262-w
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in 3D imaging technologies provide novel insights to researchers and reveal finer and more detail of examined specimen, especially in the biomedical domain, but also impose huge challenges regarding scalability for automated analysis algorithms due to rapidly increasing dataset sizes. In particular, e...
[ { "created": "Fri, 5 Feb 2021 23:13:09 GMT", "version": "v1" } ]
2021-06-30
[ [ "Drees", "Dominik", "" ], [ "Scherzinger", "Aaron", "" ], [ "Hägerling", "René", "" ], [ "Kiefer", "Friedemann", "" ], [ "Jiang", "Xiaoyi", "" ] ]
2102.03502
Zhenhan Huang
Zhenhan Huang, Fumihide Tanaka
MSPM: A Modularized and Scalable Multi-Agent Reinforcement Learning-based System for Financial Portfolio Management
null
PLoS ONE 17(2): e0263689 (2022)
10.1371/journal.pone.0263689
null
q-fin.PM cs.AI cs.LG q-fin.CP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Financial portfolio management (PM) is one of the most applicable problems in reinforcement learning (RL) owing to its sequential decision-making nature. However, existing RL-based approaches rarely focus on scalability or reusability to adapt to the ever-changing markets. These approaches are rigid and unscalable to...
[ { "created": "Sat, 6 Feb 2021 04:04:57 GMT", "version": "v1" }, { "created": "Tue, 9 Feb 2021 16:19:01 GMT", "version": "v2" }, { "created": "Fri, 11 Jun 2021 08:42:30 GMT", "version": "v3" }, { "created": "Sat, 19 Feb 2022 03:54:41 GMT", "version": "v4" } ]
2022-02-22
[ [ "Huang", "Zhenhan", "" ], [ "Tanaka", "Fumihide", "" ] ]
2102.03752
Yusheng Su
Yusheng Su, Xu Han, Yankai Lin, Zhengyan Zhang, Zhiyuan Liu, Peng Li, Jie Zhou, Maosong Sun
CSS-LM: A Contrastive Framework for Semi-supervised Fine-tuning of Pre-trained Language Models
null
IEEE/ACM Transactions on Audio, Speech, and Language Processing 2021
10.1109/TASLP.2021.3105013
2329-9290
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Fine-tuning pre-trained language models (PLMs) has demonstrated its effectiveness on various downstream NLP tasks recently. However, in many low-resource scenarios, the conventional fine-tuning strategies cannot sufficiently capture the important semantic features for downstream tasks. To address this issue, we intro...
[ { "created": "Sun, 7 Feb 2021 09:27:26 GMT", "version": "v1" }, { "created": "Mon, 1 Mar 2021 08:50:38 GMT", "version": "v2" }, { "created": "Wed, 3 Mar 2021 11:47:00 GMT", "version": "v3" } ]
2021-11-15
[ [ "Su", "Yusheng", "" ], [ "Han", "Xu", "" ], [ "Lin", "Yankai", "" ], [ "Zhang", "Zhengyan", "" ], [ "Liu", "Zhiyuan", "" ], [ "Li", "Peng", "" ], [ "Zhou", "Jie", "" ], [ "Sun", "Maosong", "...
2102.03814
Theerawit Wilaiprasitporn
Phairot Autthasan, Rattanaphon Chaisaen, Thapanun Sudhawiyangkul, Phurin Rangpong, Suktipol Kiatthaveephong, Nat Dilokthanakul, Gun Bhakdisongkhram, Huy Phan, Cuntai Guan and Theerawit Wilaiprasitporn
MIN2Net: End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification
null
IEEE Transactions on Biomedical Engineering 2021
10.1109/TBME.2021.3137184
null
eess.SP cs.AI cs.CV cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
Advances in the motor imagery (MI)-based brain-computer interfaces (BCIs) allow control of several applications by decoding neurophysiological phenomena, which are usually recorded by electroencephalography (EEG) using a non-invasive technique. Despite great advances in MI-based BCI, EEG rhythms are specific to a sub...
[ { "created": "Sun, 7 Feb 2021 15:20:23 GMT", "version": "v1" }, { "created": "Sun, 16 May 2021 08:03:59 GMT", "version": "v2" }, { "created": "Thu, 20 May 2021 09:48:47 GMT", "version": "v3" }, { "created": "Fri, 7 Jan 2022 17:20:56 GMT", "version": "v4" } ]
2022-01-10
[ [ "Autthasan", "Phairot", "" ], [ "Chaisaen", "Rattanaphon", "" ], [ "Sudhawiyangkul", "Thapanun", "" ], [ "Rangpong", "Phurin", "" ], [ "Kiatthaveephong", "Suktipol", "" ], [ "Dilokthanakul", "Nat", "" ], [ "Bhakdis...
2102.03858
Zaharah A. Bukhsh
Zaharah A. Bukhsh, Nils Jansen, Aaqib Saeed
Damage detection using in-domain and cross-domain transfer learning
16 pages, 8 figures, 7 tables
Neural Comput & Applic (2021)
10.1007/s00521-021-06279-x
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the capabilities of transfer learning in the area of structural health monitoring. In particular, we are interested in damage detection for concrete structures. Typical image datasets for such problems are relatively small, calling for the transfer of learned representation from a related large-scale d...
[ { "created": "Sun, 7 Feb 2021 17:36:27 GMT", "version": "v1" }, { "created": "Tue, 5 Oct 2021 09:37:22 GMT", "version": "v2" } ]
2021-10-06
[ [ "Bukhsh", "Zaharah A.", "" ], [ "Jansen", "Nils", "" ], [ "Saeed", "Aaqib", "" ] ]
2102.03896
Simon Zhuang
Simon Zhuang, Dylan Hadfield-Menell
Consequences of Misaligned AI
null
NeurIPS 2020
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
AI systems often rely on two key components: a specified goal or reward function and an optimization algorithm to compute the optimal behavior for that goal. This approach is intended to provide value for a principal: the user on whose behalf the agent acts. The objectives given to these agents often refer to a parti...
[ { "created": "Sun, 7 Feb 2021 19:34:04 GMT", "version": "v1" } ]
2021-02-09
[ [ "Zhuang", "Simon", "" ], [ "Hadfield-Menell", "Dylan", "" ] ]
2102.03897
Chetan Srinidhi L
Chetan L. Srinidhi, Seung Wook Kim, Fu-Der Chen, Anne L. Martel
Self-supervised driven consistency training for annotation efficient histopathology image analysis
null
Medical Image Analysis, Volume 75, January 2022
10.1016/j.media.2021.102256
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Training a neural network with a large labeled dataset is still a dominant paradigm in computational histopathology. However, obtaining such exhaustive manual annotations is often expensive, laborious, and prone to inter and Intra-observer variability. While recent self-supervised and semi-supervised methods can alle...
[ { "created": "Sun, 7 Feb 2021 19:46:21 GMT", "version": "v1" }, { "created": "Tue, 9 Feb 2021 23:26:44 GMT", "version": "v2" }, { "created": "Sun, 3 Oct 2021 11:07:40 GMT", "version": "v3" } ]
2021-11-03
[ [ "Srinidhi", "Chetan L.", "" ], [ "Kim", "Seung Wook", "" ], [ "Chen", "Fu-Der", "" ], [ "Martel", "Anne L.", "" ] ]
2102.03932
Fazael Ayatollahi
Fazael Ayatollahi (1 and 2), Shahriar B. Shokouhi (1), Ritse M. Mann (2), Jonas Teuwen (2 and 3) ((1) Electrical Engineering Department, Iran University of Science and Technology (IUST), Tehran, Iran, (2) Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands,...
Automatic Breast Lesion Detection in Ultrafast DCE-MRI Using Deep Learning
null
Medical physics vol. 48,10 (2021): 5897-5907
10.1002/mp.15156
null
eess.IV cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
Purpose: We propose a deep learning-based computer-aided detection (CADe) method to detect breast lesions in ultrafast DCE-MRI sequences. This method uses both the three-dimensional spatial information and temporal information obtained from the early-phase of the dynamic acquisition. Methods: The proposed CADe method...
[ { "created": "Sun, 7 Feb 2021 22:03:39 GMT", "version": "v1" }, { "created": "Sun, 15 Aug 2021 19:47:00 GMT", "version": "v2" } ]
2021-11-12
[ [ "Ayatollahi", "Fazael", "", "1 and 2" ], [ "Shokouhi", "Shahriar B.", "", "2 and 3" ], [ "Mann", "Ritse M.", "", "2 and 3" ], [ "Teuwen", "Jonas", "", "2 and 3" ] ]
2102.04034
Andrew Palmer
Andrew W. Palmer, Albi Sema, Wolfram Martens, Peter Rudolph and Wolfgang Waizenegger
The Autonomous Siemens Tram
6 pages, presented at the 2020 International Conference on Intelligent Transportation Systems (ITSC)
A. W. Palmer, A. Sema, W. Martens, P. Rudolph and W. Waizenegger, "The Autonomous Siemens Tram," 2020 IEEE 23rd ITSC, 2020, pp. 1-6
10.1109/ITSC45102.2020.9294699
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents the Autonomous Siemens Tram that was publicly demonstrated in Potsdam, Germany during the InnoTrans 2018 exhibition. The system was built on a Siemens Combino tram and used a multi-modal sensor suite to localize the vehicle, and to detect and respond to traffic signals and obstacles. An overview o...
[ { "created": "Mon, 8 Feb 2021 07:13:58 GMT", "version": "v1" } ]
2021-02-09
[ [ "Palmer", "Andrew W.", "" ], [ "Sema", "Albi", "" ], [ "Martens", "Wolfram", "" ], [ "Rudolph", "Peter", "" ], [ "Waizenegger", "Wolfgang", "" ] ]
2102.04060
Maxime Ferrera
Maxime Ferrera, Alexandre Eudes, Julien Moras, Martial Sanfourche, Guy Le Besnerais
OV$^{2}$SLAM : A Fully Online and Versatile Visual SLAM for Real-Time Applications
Accepted for publication in IEEE Robotics and Automation Letters (RA-L). Code is available at : \url{https://github.com/ov2slam/ov2slam}
IEEE Robotics and Automation Letters, IEEE 2021
null
null
cs.CV cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many applications of Visual SLAM, such as augmented reality, virtual reality, robotics or autonomous driving, require versatile, robust and precise solutions, most often with real-time capability. In this work, we describe OV$^{2}$SLAM, a fully online algorithm, handling both monocular and stereo camera setups, vario...
[ { "created": "Mon, 8 Feb 2021 08:39:23 GMT", "version": "v1" } ]
2021-02-09
[ [ "Ferrera", "Maxime", "" ], [ "Eudes", "Alexandre", "" ], [ "Moras", "Julien", "" ], [ "Sanfourche", "Martial", "" ], [ "Besnerais", "Guy Le", "" ] ]
2102.04201
Jennifer Cobbe Dr
Jennifer Cobbe, Michelle Seng Ah Lee, Jatinder Singh
Reviewable Automated Decision-Making: A Framework for Accountable Algorithmic Systems
null
ACM Conference on Fairness, Accountability, and Transparency (FAccT 21), March 2021, Virtual Event, Canada
null
null
cs.CY cs.AI
http://creativecommons.org/licenses/by/4.0/
This paper introduces reviewability as a framework for improving the accountability of automated and algorithmic decision-making (ADM) involving machine learning. We draw on an understanding of ADM as a socio-technical process involving both human and technical elements, beginning before a decision is made and extend...
[ { "created": "Tue, 26 Jan 2021 18:15:34 GMT", "version": "v1" }, { "created": "Wed, 10 Feb 2021 11:48:42 GMT", "version": "v2" } ]
2021-02-11
[ [ "Cobbe", "Jennifer", "" ], [ "Lee", "Michelle Seng Ah", "" ], [ "Singh", "Jatinder", "" ] ]
2102.04202
Shoffan Saifullah
Shoffan Saifullah
Segmentasi Citra Menggunakan Metode Watershed Transform Berdasarkan Image Enhancement Dalam Mendeteksi Embrio Telur
8 pages, in Indonesian language, 6 figures
Systemic: Information System and Informatics Journal, 5(2), (2019), 53-60
10.29080/systemic.v5i2.798
null
eess.IV cs.CV
http://creativecommons.org/licenses/by/4.0/
Image processing can be applied in the detection of egg embryos. The egg embryos detection is processed using a segmentation process. The segmentation divides the image according to the area that is divided. This process requires improvement of the image that is processed to obtain optimal results. This study will an...
[ { "created": "Mon, 8 Feb 2021 14:03:51 GMT", "version": "v1" } ]
2021-02-14
[ [ "Saifullah", "Shoffan", "" ] ]
2102.04216
Anusha Bompelli
Anusha Bompelli, Yanshan Wang, Ruyuan Wan, Esha Singh, Yuqi Zhou, Lin Xu, David Oniani, Bhavani Singh Agnikula Kshatriya, Joyce (Joy) E. Balls-Berry, and Rui Zhang
Social and behavioral determinants of health in the era of artificial intelligence with electronic health records: A scoping review
32 pages, 5 figures
Health Data Science. 2021 Aug 24;2021:9759016
10.34133/2021/9759016
Article ID 9759016
cs.CY cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Background: There is growing evidence that social and behavioral determinants of health (SBDH) play a substantial effect in a wide range of health outcomes. Electronic health records (EHRs) have been widely employed to conduct observational studies in the age of artificial intelligence (AI). However, there has been l...
[ { "created": "Fri, 22 Jan 2021 09:03:39 GMT", "version": "v1" }, { "created": "Sun, 13 Jun 2021 17:50:11 GMT", "version": "v2" } ]
2021-10-12
[ [ "Bompelli", "Anusha", "", "Joy" ], [ "Wang", "Yanshan", "", "Joy" ], [ "Wan", "Ruyuan", "", "Joy" ], [ "Singh", "Esha", "", "Joy" ], [ "Zhou", "Yuqi", "", "Joy" ], [ "Xu", "Lin", "", "Joy" ], [ ...
2102.04341
Jonathan Kelly
Justin Tomasi, Brandon Wagstaff, Steven L. Waslander, Jonathan Kelly
Learned Camera Gain and Exposure Control for Improved Visual Feature Detection and Matching
In IEEE Robotics and Automation Letters (RA-L) and presented at the IEEE International Conference on Robotics and Automation (ICRA'21), Xi'an, China, May 30-Jun. 5, 2021
IEEE Robotics and Automation Letters (RA-L), Vol. 6, No. 2, pp. 2028-2035, Apr. 2021
10.1109/LRA.2021.3058909
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Successful visual navigation depends upon capturing images that contain sufficient useful information. In this letter, we explore a data-driven approach to account for environmental lighting changes, improving the quality of images for use in visual odometry (VO) or visual simultaneous localization and mapping (SLAM)...
[ { "created": "Mon, 8 Feb 2021 16:46:09 GMT", "version": "v1" }, { "created": "Sun, 28 Feb 2021 17:52:10 GMT", "version": "v2" }, { "created": "Mon, 11 Jul 2022 05:00:57 GMT", "version": "v3" } ]
2022-07-12
[ [ "Tomasi", "Justin", "" ], [ "Wagstaff", "Brandon", "" ], [ "Waslander", "Steven L.", "" ], [ "Kelly", "Jonathan", "" ] ]
2102.04366
Lucas Prado Osco
Mauro dos Santos de Arruda, Lucas Prado Osco, Plabiany Rodrigo Acosta, Diogo Nunes Gon\c{c}alves, Jos\'e Marcato Junior, Ana Paula Marques Ramos, Edson Takashi Matsubara, Zhipeng Luo, Jonathan Li, Jonathan de Andrade Silva, Wesley Nunes Gon\c{c}alves
Counting and Locating High-Density Objects Using Convolutional Neural Network
15 pages, 10 figures, 8 tables
Expert Systems with Applications, 2022
10.1016/j.eswa.2022.116555
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
This paper presents a Convolutional Neural Network (CNN) approach for counting and locating objects in high-density imagery. To the best of our knowledge, this is the first object counting and locating method based on a feature map enhancement and a Multi-Stage Refinement of the confidence map. The proposed method wa...
[ { "created": "Mon, 8 Feb 2021 17:17:10 GMT", "version": "v1" } ]
2022-05-31
[ [ "de Arruda", "Mauro dos Santos", "" ], [ "Osco", "Lucas Prado", "" ], [ "Acosta", "Plabiany Rodrigo", "" ], [ "Gonçalves", "Diogo Nunes", "" ], [ "Junior", "José Marcato", "" ], [ "Ramos", "Ana Paula Marques", "" ], [ ...
2102.04394
Fabio Gonzalez
Fabio A. Gonz\'alez, Alejandro Gallego, Santiago Toledo-Cort\'es, Vladimir Vargas-Calder\'on
Learning with Density Matrices and Random Features
Final version published in Quantum Mach. Intell. 4, 23 (2022)
Quantum Mach. Intell. 4, 23 (2022)
10.1007/s42484-022-00079-9
null
cs.LG cs.AI quant-ph
http://creativecommons.org/licenses/by-sa/4.0/
A density matrix describes the statistical state of a quantum system. It is a powerful formalism to represent both the quantum and classical uncertainty of quantum systems and to express different statistical operations such as measurement, system combination and expectations as linear algebra operations. This paper ...
[ { "created": "Mon, 8 Feb 2021 17:54:59 GMT", "version": "v1" }, { "created": "Fri, 12 Feb 2021 14:40:04 GMT", "version": "v2" }, { "created": "Tue, 21 Sep 2021 01:40:47 GMT", "version": "v3" }, { "created": "Tue, 9 Nov 2021 04:05:52 GMT", "version": "v4" }, { "cre...
2024-05-01
[ [ "González", "Fabio A.", "" ], [ "Gallego", "Alejandro", "" ], [ "Toledo-Cortés", "Santiago", "" ], [ "Vargas-Calderón", "Vladimir", "" ] ]
2102.04402
Xueguang Lyu
Xueguang Lyu, Yuchen Xiao, Brett Daley, Christopher Amato
Contrasting Centralized and Decentralized Critics in Multi-Agent Reinforcement Learning
null
Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS). 2021
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
Centralized Training for Decentralized Execution, where agents are trained offline using centralized information but execute in a decentralized manner online, has gained popularity in the multi-agent reinforcement learning community. In particular, actor-critic methods with a centralized critic and decentralized acto...
[ { "created": "Mon, 8 Feb 2021 18:08:11 GMT", "version": "v1" }, { "created": "Thu, 2 Dec 2021 21:33:13 GMT", "version": "v2" } ]
2021-12-06
[ [ "Lyu", "Xueguang", "" ], [ "Xiao", "Yuchen", "" ], [ "Daley", "Brett", "" ], [ "Amato", "Christopher", "" ] ]
2102.04566
Lucas Prado Osco
Patrik Ol\~a Bressan, Jos\'e Marcato Junior, Jos\'e Augusto Correa Martins, Diogo Nunes Gon\c{c}alves, Daniel Matte Freitas, Lucas Prado Osco, Jonathan de Andrade Silva, Zhipeng Luo, Jonathan Li, Raymundo Cordero Garcia, Wesley Nunes Gon\c{c}alves
Semantic Segmentation with Labeling Uncertainty and Class Imbalance
15 pages, 9 figures, 3 tables
International Journal of Applied Earth Observation and Geoinformation, 2022
10.1016/j.jag.2022.102690
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Recently, methods based on Convolutional Neural Networks (CNN) achieved impressive success in semantic segmentation tasks. However, challenges such as the class imbalance and the uncertainty in the pixel-labeling process are not completely addressed. As such, we present a new approach that calculates a weight for eac...
[ { "created": "Mon, 8 Feb 2021 22:53:33 GMT", "version": "v1" } ]
2022-05-31
[ [ "Bressan", "Patrik Olã", "" ], [ "Junior", "José Marcato", "" ], [ "Martins", "José Augusto Correa", "" ], [ "Gonçalves", "Diogo Nunes", "" ], [ "Freitas", "Daniel Matte", "" ], [ "Osco", "Lucas Prado", "" ], [ "Si...
2102.04652
Xiangzeng Zhou
Xiangzeng Zhou and Pan Pan and Yun Zheng and Yinghui Xu and Rong Jin
Large Scale Long-tailed Product Recognition System at Alibaba
Acccepted by CIKM 2020
In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM20), 3353-3356 (2020)
10.1145/3340531.3417445
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A practical large scale product recognition system suffers from the phenomenon of long-tailed imbalanced training data under the E-commercial circumstance at Alibaba. Besides product images at Alibaba, plenty of image related side information (e.g. title, tags) reveal rich semantic information about images. Prior wor...
[ { "created": "Tue, 9 Feb 2021 05:34:30 GMT", "version": "v1" } ]
2021-02-10
[ [ "Zhou", "Xiangzeng", "" ], [ "Pan", "Pan", "" ], [ "Zheng", "Yun", "" ], [ "Xu", "Yinghui", "" ], [ "Jin", "Rong", "" ] ]
2102.04667
Yanhao Zhang
Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Jianmin Wu, Yinghui Xu, Rong Jin
Virtual ID Discovery from E-commerce Media at Alibaba: Exploiting Richness of User Click Behavior for Visual Search Relevance
accepted by CIKM 2019
CIKM 2019: 2489-2497
10.1145/3357384.3357800
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Visual search plays an essential role for E-commerce. To meet the search demands of users and promote shopping experience at Alibaba, visual search relevance of real-shot images is becoming the bottleneck. Traditional visual search paradigm is usually based upon supervised learning with labeled data. However, large-s...
[ { "created": "Tue, 9 Feb 2021 06:31:20 GMT", "version": "v1" } ]
2021-02-10
[ [ "Zhang", "Yanhao", "" ], [ "Pan", "Pan", "" ], [ "Zheng", "Yun", "" ], [ "Zhao", "Kang", "" ], [ "Wu", "Jianmin", "" ], [ "Xu", "Yinghui", "" ], [ "Jin", "Rong", "" ] ]
2102.04674
Yanhao Zhang
Yanhao Zhang, Pan Pan, Yun Zheng, Kang Zhao, Yingya Zhang, Xiaofeng Ren, Rong Jin
Visual Search at Alibaba
accepted by KDD 2018
KDD 2018: 993-1001
10.1145/3219819.3219820
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper introduces the large scale visual search algorithm and system infrastructure at Alibaba. The following challenges are discussed under the E-commercial circumstance at Alibaba (a) how to handle heterogeneous image data and bridge the gap between real-shot images from user query and the online images. (b) ho...
[ { "created": "Tue, 9 Feb 2021 06:46:50 GMT", "version": "v1" } ]
2021-02-10
[ [ "Zhang", "Yanhao", "" ], [ "Pan", "Pan", "" ], [ "Zheng", "Yun", "" ], [ "Zhao", "Kang", "" ], [ "Zhang", "Yingya", "" ], [ "Ren", "Xiaofeng", "" ], [ "Jin", "Rong", "" ] ]
2102.04780
Sutharsan Mahendren Mr
Sutharsan Mahendren, Chamira Edussooriya, Ranga Rodrigo
Diverse Single Image Generation with Controllable Global Structure
Published in the Neurocomputing Journal
Neurocomputing 528(2023)97-112
10.1016/j.neucom.2023.01.011
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Image generation from a single image using generative adversarial networks is quite interesting due to the realism of generated images. However, recent approaches need improvement for such realistic and diverse image generation, when the global context of the image is important such as in face, animal, and architectu...
[ { "created": "Tue, 9 Feb 2021 11:52:48 GMT", "version": "v1" }, { "created": "Mon, 15 Feb 2021 05:22:34 GMT", "version": "v2" }, { "created": "Thu, 20 Jan 2022 05:25:10 GMT", "version": "v3" }, { "created": "Wed, 25 Jan 2023 13:10:39 GMT", "version": "v4" } ]
2023-01-26
[ [ "Mahendren", "Sutharsan", "" ], [ "Edussooriya", "Chamira", "" ], [ "Rodrigo", "Ranga", "" ] ]
2102.04816
Abdelrahman Abdallah
Daniyar Nurseitov, Kairat Bostanbekov, Maksat Kanatov, Anel Alimova, Abdelrahman Abdallah, Galymzhan Abdimanap
Classification of Handwritten Names of Cities and Handwritten Text Recognition using Various Deep Learning Models
null
Advances in Science, Technology and Engineering Systems. 5, 934-943 (2020)
10.25046/aj0505114
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
This article discusses the problem of handwriting recognition in Kazakh and Russian languages. This area is poorly studied since in the literature there are almost no works in this direction. We have tried to describe various approaches and achievements of recent years in the development of handwritten recognition mo...
[ { "created": "Tue, 9 Feb 2021 13:34:16 GMT", "version": "v1" } ]
2021-02-10
[ [ "Nurseitov", "Daniyar", "" ], [ "Bostanbekov", "Kairat", "" ], [ "Kanatov", "Maksat", "" ], [ "Alimova", "Anel", "" ], [ "Abdallah", "Abdelrahman", "" ], [ "Abdimanap", "Galymzhan", "" ] ]
2102.04916
Pierre Aumjaud
Pierre Aumjaud, David McAuliffe, Francisco Javier Rodr\'iguez Lera, Philip Cardiff
rl_reach: Reproducible Reinforcement Learning Experiments for Robotic Reaching Tasks
7 pages, 5 figures
Software Impacts. 8 (2021) 100061
10.1016/j.simpa.2021.100061
null
cs.LG cs.AI cs.RO
http://creativecommons.org/licenses/by-sa/4.0/
Training reinforcement learning agents at solving a given task is highly dependent on identifying optimal sets of hyperparameters and selecting suitable environment input / output configurations. This tedious process could be eased with a straightforward toolbox allowing its user to quickly compare different training...
[ { "created": "Tue, 9 Feb 2021 16:14:10 GMT", "version": "v1" }, { "created": "Mon, 1 Mar 2021 19:32:01 GMT", "version": "v2" } ]
2021-03-03
[ [ "Aumjaud", "Pierre", "" ], [ "McAuliffe", "David", "" ], [ "Lera", "Francisco Javier Rodríguez", "" ], [ "Cardiff", "Philip", "" ] ]
2102.04993
Marc G\'orriz Blanch
Marc G\'orriz, Saverio Blasi, Alan F. Smeaton, Noel E. O'Connor, Marta Mrak
Attention-Based Neural Networks for Chroma Intra Prediction in Video Coding
null
IEEE Journal of Selected Topics in Signal Processing, 2020
10.1109/JSTSP.2020.3044482
null
eess.IV cs.CC cs.CV cs.LG cs.MM
http://creativecommons.org/licenses/by-nc-sa/4.0/
Neural networks can be successfully used to improve several modules of advanced video coding schemes. In particular, compression of colour components was shown to greatly benefit from usage of machine learning models, thanks to the design of appropriate attention-based architectures that allow the prediction to explo...
[ { "created": "Tue, 9 Feb 2021 18:01:22 GMT", "version": "v1" } ]
2021-02-10
[ [ "Górriz", "Marc", "" ], [ "Blasi", "Saverio", "" ], [ "Smeaton", "Alan F.", "" ], [ "O'Connor", "Noel E.", "" ], [ "Mrak", "Marta", "" ] ]
2102.05067
Silvia Cascianelli PhD
Silvia Cascianelli, Gabriele Costante, Alessandro Devo, Thomas A. Ciarfuglia, Paolo Valigi, Mario L. Fravolini
The Role of the Input in Natural Language Video Description
In IEEE Transactions on Multimedia
IEEE Transactions on Multimedia, 22(1), 271-283 (2019)
null
null
cs.CV cs.CL cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Natural Language Video Description (NLVD) has recently received strong interest in the Computer Vision, Natural Language Processing (NLP), Multimedia, and Autonomous Robotics communities. The State-of-the-Art (SotA) approaches obtained remarkable results when tested on the benchmark datasets. However, those approache...
[ { "created": "Tue, 9 Feb 2021 19:00:35 GMT", "version": "v1" } ]
2021-02-11
[ [ "Cascianelli", "Silvia", "" ], [ "Costante", "Gabriele", "" ], [ "Devo", "Alessandro", "" ], [ "Ciarfuglia", "Thomas A.", "" ], [ "Valigi", "Paolo", "" ], [ "Fravolini", "Mario L.", "" ] ]
2102.05126
Jon\'a\v{s} Kulh\'anek
Jon\'a\v{s} Kulh\'anek and Vojt\v{e}ch Hude\v{c}ek and Tom\'a\v{s} Nekvinda and Ond\v{r}ej Du\v{s}ek
AuGPT: Auxiliary Tasks and Data Augmentation for End-To-End Dialogue with Pre-Trained Language Models
null
Proceedings of the 3rd Workshop on Natural Language Processing for Conversational AI (2021), 198-210
10.18653/v1/2021.nlp4convai-1.19
null
cs.CL cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Attention-based pre-trained language models such as GPT-2 brought considerable progress to end-to-end dialogue modelling. However, they also present considerable risks for task-oriented dialogue, such as lack of knowledge grounding or diversity. To address these issues, we introduce modified training objectives for l...
[ { "created": "Tue, 9 Feb 2021 20:53:34 GMT", "version": "v1" }, { "created": "Mon, 27 Sep 2021 08:28:40 GMT", "version": "v2" }, { "created": "Fri, 14 Jan 2022 14:42:11 GMT", "version": "v3" } ]
2022-01-17
[ [ "Kulhánek", "Jonáš", "" ], [ "Hudeček", "Vojtěch", "" ], [ "Nekvinda", "Tomáš", "" ], [ "Dušek", "Ondřej", "" ] ]