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4,300 | Many-to-Many Graph Matching: a Continuous Relaxation Approach | stat.ML | Graphs provide an efficient tool for object representation in various
computer vision applications. Once graph-based representations are constructed,
an important question is how to compare graphs. This problem is often
formulated as a graph matching problem where one seeks a mapping between
vertices of two graphs whic... | computer science |
4,301 | C-HiLasso: A Collaborative Hierarchical Sparse Modeling Framework | stat.ML | Sparse modeling is a powerful framework for data analysis and processing.
Traditionally, encoding in this framework is performed by solving an
L1-regularized linear regression problem, commonly referred to as Lasso or
Basis Pursuit. In this work we combine the sparsity-inducing property of the
Lasso model at the indivi... | computer science |
4,302 | Toward Parts-Based Scene Understanding with Pixel-Support Parts-Sparse
Pictorial Structures | cs.CV | Scene understanding remains a significant challenge in the computer vision
community. The visual psychophysics literature has demonstrated the importance
of interdependence among parts of the scene. Yet, the majority of methods in
computer vision remain local. Pictorial structures have arisen as a fundamental
parts-bas... | computer science |
4,303 | Joint-ViVo: Selecting and Weighting Visual Words Jointly for
Bag-of-Features based Tissue Classification in Medical Images | cs.CV | Automatically classifying the tissues types of Region of Interest (ROI) in
medical imaging has been an important application in Computer-Aided Diagnosis
(CAD), such as classification of breast parenchymal tissue in the mammogram,
classify lung disease patterns in High-Resolution Computed Tomography (HRCT)
etc. Recently... | computer science |
4,304 | A Unified Approach for Modeling and Recognition of Individual Actions
and Group Activities | cs.CV | Recognizing group activities is challenging due to the difficulties in
isolating individual entities, finding the respective roles played by the
individuals and representing the complex interactions among the participants.
Individual actions and group activities in videos can be represented in a
common framework as the... | computer science |
4,305 | BSVM: A Banded Suport Vector Machine | stat.ML | We describe a novel binary classification technique called Banded SVM
(B-SVM). In the standard C-SVM formulation of Cortes et al. (1995), the
decision rule is encouraged to lie in the interval [1, \infty]. The new B-SVM
objective function contains a penalty term that encourages the decision rule to
lie in a user specif... | computer science |
4,306 | Hybrid Linear Modeling via Local Best-fit Flats | cs.CV | We present a simple and fast geometric method for modeling data by a union of
affine subspaces. The method begins by forming a collection of local best-fit
affine subspaces, i.e., subspaces approximating the data in local
neighborhoods. The correct sizes of the local neighborhoods are determined
automatically by the Jo... | computer science |
4,307 | Convex Approaches to Model Wavelet Sparsity Patterns | cs.CV | Statistical dependencies among wavelet coefficients are commonly represented
by graphical models such as hidden Markov trees(HMTs). However, in linear
inverse problems such as deconvolution, tomography, and compressed sensing, the
presence of a sensing or observation matrix produces a linear mixing of the
simple Markov... | computer science |
4,308 | Multi-Stage Classifier Design | cs.CV | In many classification systems, sensing modalities have different acquisition
costs. It is often {\it unnecessary} to use every modality to classify a
majority of examples. We study a multi-stage system in a prediction time cost
reduction setting, where the full data is available for training, but for a
test example, m... | computer science |
4,309 | Polarimetric SAR Image Segmentation with B-Splines and a New Statistical
Model | cs.CV | We present an approach for polarimetric Synthetic Aperture Radar (SAR) image
region boundary detection based on the use of B-Spline active contours and a
new model for polarimetric SAR data: the GHP distribution. In order to detect
the boundary of a region, initial B-Spline curves are specified, either
automatically or... | computer science |
4,310 | On the convergence of the IRLS algorithm in Non-Local Patch Regression | cs.CV | Recently, it was demonstrated in [CS2012,CS2013] that the robustness of the
classical Non-Local Means (NLM) algorithm [BCM2005] can be improved by
incorporating $\ell^p (0 < p \leq 2)$ regression into the NLM framework. This
general optimization framework, called Non-Local Patch Regression (NLPR),
contains NLM as a spe... | computer science |
4,311 | Learning Stable Multilevel Dictionaries for Sparse Representations | cs.CV | Sparse representations using learned dictionaries are being increasingly used
with success in several data processing and machine learning applications. The
availability of abundant training data necessitates the development of
efficient, robust and provably good dictionary learning algorithms. Algorithmic
stability an... | computer science |
4,312 | Sparsity Based Poisson Denoising with Dictionary Learning | cs.CV | The problem of Poisson denoising appears in various imaging applications,
such as low-light photography, medical imaging and microscopy. In cases of high
SNR, several transformations exist so as to convert the Poisson noise into an
additive i.i.d. Gaussian noise, for which many effective algorithms are
available. Howev... | computer science |
4,313 | Randomized Robust Subspace Recovery for High Dimensional Data Matrices | stat.ML | This paper explores and analyzes two randomized designs for robust Principal
Component Analysis (PCA) employing low-dimensional data sketching. In one
design, a data sketch is constructed using random column sampling followed by
low dimensional embedding, while in the other, sketching is based on random
column and row ... | computer science |
4,314 | Writer-independent Feature Learning for Offline Signature Verification
using Deep Convolutional Neural Networks | cs.CV | Automatic Offline Handwritten Signature Verification has been researched over
the last few decades from several perspectives, using insights from graphology,
computer vision, signal processing, among others. In spite of the advancements
on the field, building classifiers that can separate between genuine signatures
and... | computer science |
4,315 | A Probabilistic Adaptive Search System for Exploring the Face Space | stat.ML | Face recall is a basic human cognitive process performed routinely, e.g.,
when meeting someone and determining if we have met that person before.
Assisting a subject during face recall by suggesting candidate faces can be
challenging. One of the reasons is that the search space - the face space - is
quite large and lac... | computer science |
4,316 | Automatic post-picking using MAPPOS improves particle image detection
from Cryo-EM micrographs | stat.ML | Cryo-electron microscopy (cryo-EM) studies using single particle
reconstruction are extensively used to reveal structural information on
macromolecular complexes. Aiming at the highest achievable resolution, state of
the art electron microscopes automatically acquire thousands of high-quality
micrographs. Particles are... | computer science |
4,317 | Rotation invariants of two dimensional curves based on iterated
integrals | cs.CV | We introduce a novel class of rotation invariants of two dimensional curves
based on iterated integrals. The invariants we present are in some sense
complete and we describe an algorithm to calculate them, giving explicit
computations up to order six. We present an application to online
(stroke-trajectory based) charac... | computer science |
4,318 | Matching Image Sets via Adaptive Multi Convex Hull | cs.CV | Traditional nearest points methods use all the samples in an image set to
construct a single convex or affine hull model for classification. However,
strong artificial features and noisy data may be generated from combinations of
training samples when significant intra-class variations and/or noise occur in
the image s... | computer science |
4,319 | Multi-Shot Person Re-Identification via Relational Stein Divergence | cs.CV | Person re-identification is particularly challenging due to significant
appearance changes across separate camera views. In order to re-identify
people, a representative human signature should effectively handle differences
in illumination, pose and camera parameters. While general appearance-based
methods are modelled... | computer science |
4,320 | Random Projections on Manifolds of Symmetric Positive Definite Matrices
for Image Classification | cs.CV | Recent advances suggest that encoding images through Symmetric Positive
Definite (SPD) matrices and then interpreting such matrices as points on
Riemannian manifolds can lead to increased classification performance. Taking
into account manifold geometry is typically done via (1) embedding the
manifolds in tangent space... | computer science |
4,321 | Sparsity Based Methods for Overparameterized Variational Problems | cs.CV | Two complementary approaches have been extensively used in signal and image
processing leading to novel results, the sparse representation methodology and
the variational strategy. Recently, a new sparsity based model has been
proposed, the cosparse analysis framework, which may potentially help in
bridging sparse appr... | computer science |
4,322 | ExtremeWeather: A large-scale climate dataset for semi-supervised
detection, localization, and understanding of extreme weather events | cs.CV | Then detection and identification of extreme weather events in large-scale
climate simulations is an important problem for risk management, informing
governmental policy decisions and advancing our basic understanding of the
climate system. Recent work has shown that fully supervised convolutional
neural networks (CNNs... | computer science |
4,323 | Learning Localized Geometric Features Using 3D-CNN: An Application to
Manufacturability Analysis of Drilled Holes | cs.CV | 3D convolutional neural networks (3D-CNN) have been used for object
recognition based on the voxelized shape of an object. In this paper, we
present a 3D-CNN based method to learn distinct local geometric features of
interest within an object. In this context, the voxelized representation may
not be sufficient to captu... | computer science |
4,324 | Multi-source Transfer Learning with Convolutional Neural Networks for
Lung Pattern Analysis | cs.CV | Early diagnosis of interstitial lung diseases is crucial for their treatment,
but even experienced physicians find it difficult, as their clinical
manifestations are similar. In order to assist with the diagnosis,
computer-aided diagnosis (CAD) systems have been developed. These commonly rely
on a fixed scale classifie... | computer science |
4,325 | Permutation-equivariant neural networks applied to dynamics prediction | cs.CV | The introduction of convolutional layers greatly advanced the performance of
neural networks on image tasks due to innately capturing a way of encoding and
learning translation-invariant operations, matching one of the underlying
symmetries of the image domain. In comparison, there are a number of problems
in which the... | computer science |
4,326 | Partial Membership Latent Dirichlet Allocation | cs.CV | Topic models (e.g., pLSA, LDA, sLDA) have been widely used for segmenting
imagery. However, these models are confined to crisp segmentation, forcing a
visual word (i.e., an image patch) to belong to one and only one topic. Yet,
there are many images in which some regions cannot be assigned a crisp
categorical label (e.... | computer science |
4,327 | Quantum Clustering and Gaussian Mixtures | stat.ML | The mixture of Gaussian distributions, a soft version of k-means , is
considered a state-of-the-art clustering algorithm. It is widely used in
computer vision for selecting classes, e.g., color, texture, and shapes. In
this algorithm, each class is described by a Gaussian distribution, defined by
its mean and covarianc... | computer science |
4,328 | Cross-Domain Sparse Coding | cs.CV | Sparse coding has shown its power as an effective data representation method.
However, up to now, all the sparse coding approaches are limited within the
single domain learning problem. In this paper, we extend the sparse coding to
cross domain learning problem, which tries to learn from a source domain to a
target dom... | computer science |
4,329 | Scalable Object Detection using Deep Neural Networks | cs.CV | Deep convolutional neural networks have recently achieved state-of-the-art
performance on a number of image recognition benchmarks, including the ImageNet
Large-Scale Visual Recognition Challenge (ILSVRC-2012). The winning model on
the localization sub-task was a network that predicts a single bounding box and
a confid... | computer science |
4,330 | Zero Shot Recognition with Unreliable Attributes | cs.CV | In principle, zero-shot learning makes it possible to train a recognition
model simply by specifying the category's attributes. For example, with
classifiers for generic attributes like \emph{striped} and \emph{four-legged},
one can construct a classifier for the zebra category by enumerating which
properties it posses... | computer science |
4,331 | Learning to Transfer Privileged Information | cs.CV | We introduce a learning framework called learning using privileged
information (LUPI) to the computer vision field. We focus on the prototypical
computer vision problem of teaching computers to recognize objects in images.
We want the computers to be able to learn faster at the expense of providing
extra information du... | computer science |
4,332 | Zero-Shot Object Recognition System based on Topic Model | cs.CV | Object recognition systems usually require fully complete manually labeled
training data to train the classifier. In this paper, we study the problem of
object recognition where the training samples are missing during the classifier
learning stage, a task also known as zero-shot learning. We propose a novel
zero-shot l... | computer science |
4,333 | A Fusion Approach for Efficient Human Skin Detection | cs.CV | A reliable human skin detection method that is adaptable to different human
skin colours and illu- mination conditions is essential for better human skin
segmentation. Even though different human skin colour detection solutions have
been successfully applied, they are prone to false skin detection and are not
able to c... | computer science |
4,334 | Enhanced Random Forest with Image/Patch-Level Learning for Image
Understanding | cs.CV | Image understanding is an important research domain in the computer vision
due to its wide real-world applications. For an image understanding framework
that uses the Bag-of-Words model representation, the visual codebook is an
essential part. Random forest (RF) as a tree-structure discriminative codebook
has been a po... | computer science |
4,335 | Crowd Saliency Detection via Global Similarity Structure | cs.CV | It is common for CCTV operators to overlook inter- esting events taking place
within the crowd due to large number of people in the crowded scene (i.e.
marathon, rally). Thus, there is a dire need to automate the detection of
salient crowd regions acquiring immediate attention for a more effective and
proactive surveil... | computer science |
4,336 | Randomized Structural Sparsity via Constrained Block Subsampling for
Improved Sensitivity of Discriminative Voxel Identification | cs.CV | In this paper, we consider voxel selection for functional Magnetic Resonance
Imaging (fMRI) brain data with the aim of finding a more complete set of
probably correlated discriminative voxels, thus improving interpretation of the
discovered potential biomarkers. The main difficulty in doing this is an
extremely high di... | computer science |
4,337 | Capturing spatial interdependence in image features: the counting grid,
an epitomic representation for bags of features | cs.CV | In recent scene recognition research images or large image regions are often
represented as disorganized "bags" of features which can then be analyzed using
models originally developed to capture co-variation of word counts in text.
However, image feature counts are likely to be constrained in different ways
than word ... | computer science |
4,338 | A Solution for Multi-Alignment by Transformation Synchronisation | cs.CV | The alignment of a set of objects by means of transformations plays an
important role in computer vision. Whilst the case for only two objects can be
solved globally, when multiple objects are considered usually iterative methods
are used. In practice the iterative methods perform well if the relative
transformations b... | computer science |
4,339 | Zero-Aliasing Correlation Filters for Object Recognition | cs.CV | Correlation filters (CFs) are a class of classifiers that are attractive for
object localization and tracking applications. Traditionally, CFs have been
designed in the frequency domain using the discrete Fourier transform (DFT),
where correlation is efficiently implemented. However, existing CF designs do
not account ... | computer science |
4,340 | On Coarse Graining of Information and Its Application to Pattern
Recognition | cs.CV | We propose a method based on finite mixture models for classifying a set of
observations into number of different categories. In order to demonstrate the
method, we show how the component densities for the mixture model can be
derived by using the maximum entropy method in conjunction with conservation of
Pythagorean m... | computer science |
4,341 | Data Representation using the Weyl Transform | cs.CV | The Weyl transform is introduced as a rich framework for data representation.
Transform coefficients are connected to the Walsh-Hadamard transform of
multiscale autocorrelations, and different forms of dyadic periodicity in a
signal are shown to appear as different features in its Weyl coefficients. The
Weyl transform ... | computer science |
4,342 | Pairwise Rotation Hashing for High-dimensional Features | cs.CV | Binary Hashing is widely used for effective approximate nearest neighbors
search. Even though various binary hashing methods have been proposed, very few
methods are feasible for extremely high-dimensional features often used in
visual tasks today. We propose a novel highly sparse linear hashing method
based on pairwis... | computer science |
4,343 | The Approximation of the Dissimilarity Projection | stat.ML | Diffusion magnetic resonance imaging (dMRI) data allow to reconstruct the 3D
pathways of axons within the white matter of the brain as a tractography. The
analysis of tractographies has drawn attention from the machine learning and
pattern recognition communities providing novel challenges such as finding an
appropriat... | computer science |
4,344 | Computational Cost Reduction in Learned Transform Classifications | cs.CV | We present a theoretical analysis and empirical evaluations of a novel set of
techniques for computational cost reduction of classifiers that are based on
learned transform and soft-threshold. By modifying optimization procedures for
dictionary and classifier training, as well as the resulting dictionary
entries, our t... | computer science |
4,345 | Tree-Cut for Probabilistic Image Segmentation | stat.ML | This paper presents a new probabilistic generative model for image
segmentation, i.e. the task of partitioning an image into homogeneous regions.
Our model is grounded on a mid-level image representation, called a region
tree, in which regions are recursively split into subregions until superpixels
are reached. Given t... | computer science |
4,346 | Offline Handwritten Signature Verification - Literature Review | cs.CV | The area of Handwritten Signature Verification has been broadly researched in
the last decades, but remains an open research problem. The objective of
signature verification systems is to discriminate if a given signature is
genuine (produced by the claimed individual), or a forgery (produced by an
impostor). This has ... | computer science |
4,347 | Automatic Extraction of the Passing Strategies of Soccer Teams | cs.CV | Technology offers new ways to measure the locations of the players and of the
ball in sports. This translates to the trajectories the ball takes on the field
as a result of the tactics the team applies. The challenge professionals in
soccer are facing is to take the reverse path: given the trajectories of the
ball is i... | computer science |
4,348 | Tumor Motion Tracking in Liver Ultrasound Images Using Mean Shift and
Active Contour | cs.CV | In this paper we present a new method for motion tracking of tumors in liver
ultrasound image sequences. Our algorithm has two main steps. In the first
step, we apply mean shift algorithm with multiple features to estimate the
center of the target in each frame. Target in the first frame is defined using
an ellipse. Ed... | computer science |
4,349 | An On-line Variational Bayesian Model for Multi-Person Tracking from
Cluttered Scenes | cs.CV | Object tracking is an ubiquitous problem that appears in many applications
such as remote sensing, audio processing, computer vision, human-machine
interfaces, human-robot interaction, etc. Although thoroughly investigated in
computer vision, tracking a time-varying number of persons remains a
challenging open problem.... | computer science |
4,350 | Zero-Shot Learning via Semantic Similarity Embedding | cs.CV | In this paper we consider a version of the zero-shot learning problem where
seen class source and target domain data are provided. The goal during
test-time is to accurately predict the class label of an unseen target domain
instance based on revealed source domain side information (\eg attributes) for
unseen classes. ... | computer science |
4,351 | Group Membership Prediction | cs.CV | The group membership prediction (GMP) problem involves predicting whether or
not a collection of instances share a certain semantic property. For instance,
in kinship verification given a collection of images, the goal is to predict
whether or not they share a {\it familial} relationship. In this context we
propose a n... | computer science |
4,352 | Partial Membership Latent Dirichlet Allocation | stat.ML | Topic models (e.g., pLSA, LDA, SLDA) have been widely used for segmenting
imagery. These models are confined to crisp segmentation. Yet, there are many
images in which some regions cannot be assigned a crisp label (e.g., transition
regions between a foggy sky and the ground or between sand and water at a
beach). In the... | computer science |
4,353 | Fast clustering for scalable statistical analysis on structured images | stat.ML | The use of brain images as markers for diseases or behavioral differences is
challenged by the small effects size and the ensuing lack of power, an issue
that has incited researchers to rely more systematically on large cohorts.
Coupled with resolution increases, this leads to very large datasets. A
striking example in... | computer science |
4,354 | Cross-scale predictive dictionaries | cs.CV | We propose a novel signal model, based on sparse representations, that
captures cross-scale features for visual signals. We show that cross-scale
predictive model enables faster solutions to sparse approximation problems.
This is achieved by first solving the sparse approximation problem for the
downsampled signal and ... | computer science |
4,355 | Domain Adaptation and Transfer Learning in StochasticNets | cs.CV | Transfer learning is a recent field of machine learning research that aims to
resolve the challenge of dealing with insufficient training data in the domain
of interest. This is a particular issue with traditional deep neural networks
where a large amount of training data is needed. Recently, StochasticNets was
propose... | computer science |
4,356 | Blind Image Denoising via Dependent Dirichlet Process Tree | cs.CV | Most existing image denoising approaches assumed the noise to be homogeneous
white Gaussian distributed with known intensity. However, in real noisy images,
the noise models are usually unknown beforehand and can be much more complex.
This paper addresses this problem and proposes a novel blind image denoising
algorith... | computer science |
4,357 | An Overview of Melanoma Detection in Dermoscopy Images Using Image
Processing and Machine Learning | cs.CV | The incidence of malignant melanoma continues to increase worldwide. This
cancer can strike at any age; it is one of the leading causes of loss of life
in young persons. Since this cancer is visible on the skin, it is potentially
detectable at a very early stage when it is curable. New developments have
converged to ma... | computer science |
4,358 | Dimensionality Reduction via Regression in Hyperspectral Imagery | stat.ML | This paper introduces a new unsupervised method for dimensionality reduction
via regression (DRR). The algorithm belongs to the family of invertible
transforms that generalize Principal Component Analysis (PCA) by using
curvilinear instead of linear features. DRR identifies the nonlinear features
through multivariate r... | computer science |
4,359 | Image Denoising with Kernels based on Natural Image Relations | cs.CV | A successful class of image denoising methods is based on Bayesian approaches
working in wavelet representations. However, analytical estimates can be
obtained only for particular combinations of analytical models of signal and
noise, thus precluding its straightforward extension to deal with other
arbitrary noise sour... | computer science |
4,360 | A Framework for Fast Image Deconvolution with Incomplete Observations | cs.CV | In image deconvolution problems, the diagonalization of the underlying
operators by means of the FFT usually yields very large speedups. When there
are incomplete observations (e.g., in the case of unknown boundaries), standard
deconvolution techniques normally involve non-diagonalizable operators,
resulting in rather ... | computer science |
4,361 | Shape-aware Surface Reconstruction from Sparse 3D Point-Clouds | cs.CV | The reconstruction of an object's shape or surface from a set of 3D points
plays an important role in medical image analysis, e.g. in anatomy
reconstruction from tomographic measurements or in the process of aligning
intra-operative navigation and preoperative planning data. In such scenarios,
one usually has to deal w... | computer science |
4,362 | Discriminative models for robust image classification | stat.ML | A variety of real-world tasks involve the classification of images into
pre-determined categories. Designing image classification algorithms that
exhibit robustness to acquisition noise and image distortions, particularly
when the available training data are insufficient to learn accurate models, is
a significant chall... | computer science |
4,363 | Kernelized Weighted SUSAN based Fuzzy C-Means Clustering for Noisy Image
Segmentation | cs.CV | The paper proposes a novel Kernelized image segmentation scheme for noisy
images that utilizes the concept of Smallest Univalue Segment Assimilating
Nucleus (SUSAN) and incorporates spatial constraints by computing circular
colour map induced weights. Fuzzy damping coefficients are obtained for each
nucleus or center p... | computer science |
4,364 | Discovering Causal Signals in Images | stat.ML | This paper establishes the existence of observable footprints that reveal the
"causal dispositions" of the object categories appearing in collections of
images. We achieve this goal in two steps. First, we take a learning approach
to observational causal discovery, and build a classifier that achieves
state-of-the-art ... | computer science |
4,365 | Statistical Pattern Recognition for Driving Styles Based on Bayesian
Probability and Kernel Density Estimation | stat.ML | Driving styles have a great influence on vehicle fuel economy, active safety,
and drivability. To recognize driving styles of path-tracking behaviors for
different divers, a statistical pattern-recognition method is developed to deal
with the uncertainty of driving styles or characteristics based on probability
density... | computer science |
4,366 | Human Attention in Visual Question Answering: Do Humans and Deep
Networks Look at the Same Regions? | stat.ML | We conduct large-scale studies on `human attention' in Visual Question
Answering (VQA) to understand where humans choose to look to answer questions
about images. We design and test multiple game-inspired novel
attention-annotation interfaces that require the subject to sharpen regions of
a blurred image to answer a qu... | computer science |
4,367 | Interpreting extracted rules from ensemble of trees: Application to
computer-aided diagnosis of breast MRI | stat.ML | High predictive performance and ease of use and interpretability are
important requirements for the applicability of a computer-aided diagnosis
(CAD) to human reading studies. We propose a CAD system specifically designed
to be more comprehensible to the radiologist reviewing screening breast MRI
studies. Multiparametr... | computer science |
4,368 | Combining multiple resolutions into hierarchical representations for
kernel-based image classification | cs.CV | Geographic object-based image analysis (GEOBIA) framework has gained
increasing interest recently. Following this popular paradigm, we propose a
novel multiscale classification approach operating on a hierarchical image
representation built from two images at different resolutions. They capture the
same scene with diff... | computer science |
4,369 | Analyzing features learned for Offline Signature Verification using Deep
CNNs | cs.CV | Research on Offline Handwritten Signature Verification explored a large
variety of handcrafted feature extractors, ranging from graphology, texture
descriptors to interest points. In spite of advancements in the last decades,
performance of such systems is still far from optimal when we test the systems
against skilled... | computer science |
4,370 | Variational Gaussian Process Auto-Encoder for Ordinal Prediction of
Facial Action Units | stat.ML | We address the task of simultaneous feature fusion and modeling of discrete
ordinal outputs. We propose a novel Gaussian process(GP) auto-encoder modeling
approach. In particular, we introduce GP encoders to project multiple observed
features onto a latent space, while GP decoders are responsible for
reconstructing the... | computer science |
4,371 | Medical image denoising using convolutional denoising autoencoders | cs.CV | Image denoising is an important pre-processing step in medical image
analysis. Different algorithms have been proposed in past three decades with
varying denoising performances. More recently, having outperformed all
conventional methods, deep learning based models have shown a great promise.
These methods are however ... | computer science |
4,372 | Photo-Realistic Single Image Super-Resolution Using a Generative
Adversarial Network | cs.CV | Despite the breakthroughs in accuracy and speed of single image
super-resolution using faster and deeper convolutional neural networks, one
central problem remains largely unsolved: how do we recover the finer texture
details when we super-resolve at large upscaling factors? The behavior of
optimization-based super-res... | computer science |
4,373 | Real-Time Single Image and Video Super-Resolution Using an Efficient
Sub-Pixel Convolutional Neural Network | cs.CV | Recently, several models based on deep neural networks have achieved great
success in terms of both reconstruction accuracy and computational performance
for single image super-resolution. In these methods, the low resolution (LR)
input image is upscaled to the high resolution (HR) space using a single
filter, commonly... | computer science |
4,374 | A Discriminative Framework for Anomaly Detection in Large Videos | cs.CV | We address an anomaly detection setting in which training sequences are
unavailable and anomalies are scored independently of temporal ordering.
Current algorithms in anomaly detection are based on the classical density
estimation approach of learning high-dimensional models and finding
low-probability events. These al... | computer science |
4,375 | Recurrent Convolutional Networks for Pulmonary Nodule Detection in CT
Imaging | stat.ML | Computed tomography (CT) generates a stack of cross-sectional images covering
a region of the body. The visual assessment of these images for the
identification of potential abnormalities is a challenging and time consuming
task due to the large amount of information that needs to be processed. In this
article we propo... | computer science |
4,376 | Cooperative Training of Descriptor and Generator Networks | stat.ML | This paper studies the cooperative training of two probabilistic models of
signals such as images. Both models are parametrized by convolutional neural
networks (ConvNets). The first network is a descriptor network, which is an
exponential family model or an energy-based model, whose feature statistics or
energy functi... | computer science |
4,377 | Deep Learning Algorithms for Signal Recognition in Long Perimeter
Monitoring Distributed Fiber Optic Sensors | cs.CV | In this paper, we show an approach to build deep learning algorithms for
recognizing signals in distributed fiber optic monitoring and security systems
for long perimeters. Synthesizing such detection algorithms poses a non-trivial
research and development challenge, because these systems face stringent error
(type I a... | computer science |
4,378 | PCM and APCM Revisited: An Uncertainty Perspective | cs.CV | In this paper, we take a new look at the possibilistic c-means (PCM) and
adaptive PCM (APCM) clustering algorithms from the perspective of uncertainty.
This new perspective offers us insights into the clustering process, and also
provides us greater degree of flexibility. We analyze the clustering behavior
of PCM-based... | computer science |
4,379 | Conditional Image Synthesis With Auxiliary Classifier GANs | stat.ML | Synthesizing high resolution photorealistic images has been a long-standing
challenge in machine learning. In this paper we introduce new methods for the
improved training of generative adversarial networks (GANs) for image
synthesis. We construct a variant of GANs employing label conditioning that
results in 128x128 r... | computer science |
4,380 | Texture Synthesis with Spatial Generative Adversarial Networks | cs.CV | Generative adversarial networks (GANs) are a recent approach to train
generative models of data, which have been shown to work particularly well on
image data. In the current paper we introduce a new model for texture synthesis
based on GAN learning. By extending the input noise distribution space from a
single vector ... | computer science |
4,381 | The Geodesic Distance between $\mathcal{G}_I^0$ Models and its
Application to Region Discrimination | cs.CV | The $\mathcal{G}_I^0$ distribution is able to characterize different regions
in monopolarized SAR imagery. It is indexed by three parameters: the number of
looks (which can be estimated in the whole image), a scale parameter and a
texture parameter. This paper presents a new proposal for feature extraction
and region d... | computer science |
4,382 | Synthesizing Normalized Faces from Facial Identity Features | cs.CV | We present a method for synthesizing a frontal, neutral-expression image of a
person's face given an input face photograph. This is achieved by learning to
generate facial landmarks and textures from features extracted from a
facial-recognition network. Unlike previous approaches, our encoding feature
vector is largely... | computer science |
4,383 | Universal representations:The missing link between faces, text,
planktons, and cat breeds | cs.CV | With the advent of large labelled datasets and high-capacity models, the
performance of machine vision systems has been improving rapidly. However, the
technology has still major limitations, starting from the fact that different
vision problems are still solved by different models, trained from scratch or
fine-tuned o... | computer science |
4,384 | Automatic Estimation of Fetal Abdominal Circumference from Ultrasound
Images | cs.CV | Ultrasound diagnosis is routinely used in obstetrics and gynecology for fetal
biometry, and owing to its time-consuming process, there has been a great
demand for automatic estimation. However, the automated analysis of ultrasound
images is complicated because they are patient-specific, operator-dependent,
and machine-... | computer science |
4,385 | A recommender system to restore images with impulse noise | cs.CV | We build a collaborative filtering recommender system to restore images with
impulse noise for which the noisy pixels have been previously identified. We
define this recommender system in terms of a new color image representation
using three matrices that depend on the noise-free pixels of the image to
restore, and two... | computer science |
4,386 | Lossy Image Compression with Compressive Autoencoders | stat.ML | We propose a new approach to the problem of optimizing autoencoders for lossy
image compression. New media formats, changing hardware technology, as well as
diverse requirements and content types create a need for compression algorithms
which are more flexible than existing codecs. Autoencoders have the potential
to ad... | computer science |
4,387 | Indoor Localization Using Visible Light Via Fusion Of Multiple
Classifiers | stat.ML | A multiple classifiers fusion localization technique using received signal
strengths (RSSs) of visible light is proposed, in which the proposed system
transmits different intensity modulated sinusoidal signals by LEDs and the
signals received by a Photo Diode (PD) placed at various grid points. First, we
obtain some {\... | computer science |
4,388 | Indoor Localization by Fusing a Group of Fingerprints Based on Random
Forests | stat.ML | Indoor localization based on SIngle Of Fingerprint (SIOF) is rather
susceptible to the changing environment, multipath, and non-line-of-sight
(NLOS) propagation. Building SIOF is also a very time-consuming process.
Recently, we first proposed a GrOup Of Fingerprints (GOOF) to improve the
localization accuracy and reduc... | computer science |
4,389 | Prostate Cancer Diagnosis using Deep Learning with 3D Multiparametric
MRI | cs.CV | A novel deep learning architecture (XmasNet) based on convolutional neural
networks was developed for the classification of prostate cancer lesions, using
the 3D multiparametric MRI data provided by the PROSTATEx challenge. End-to-end
training was performed for XmasNet, with data augmentation done through 3D
rotation a... | computer science |
4,390 | Classification of COPD with Multiple Instance Learning | cs.CV | Chronic obstructive pulmonary disease (COPD) is a lung disease where early
detection benefits the survival rate. COPD can be quantified by classifying
patches of computed tomography images, and combining patch labels into an
overall diagnosis for the image. As labeled patches are often not available,
image labels are p... | computer science |
4,391 | Transfer Learning by Asymmetric Image Weighting for Segmentation across
Scanners | cs.CV | Supervised learning has been very successful for automatic segmentation of
images from a single scanner. However, several papers report deteriorated
performances when using classifiers trained on images from one scanner to
segment images from other scanners. We propose a transfer learning classifier
that adapts to diff... | computer science |
4,392 | Label Stability in Multiple Instance Learning | cs.CV | We address the problem of \emph{instance label stability} in multiple
instance learning (MIL) classifiers. These classifiers are trained only on
globally annotated images (bags), but often can provide fine-grained
annotations for image pixels or patches (instances). This is interesting for
computer aided diagnosis (CAD... | computer science |
4,393 | Low-rank and Sparse NMF for Joint Endmembers' Number Estimation and
Blind Unmixing of Hyperspectral Images | cs.CV | Estimation of the number of endmembers existing in a scene constitutes a
critical task in the hyperspectral unmixing process. The accuracy of this
estimate plays a crucial role in subsequent unsupervised unmixing steps i.e.,
the derivation of the spectral signatures of the endmembers (endmembers'
extraction) and the es... | computer science |
4,394 | Robust Kronecker-Decomposable Component Analysis for Low-Rank Modeling | stat.ML | Dictionary learning and component analysis are part of one of the most
well-studied and active research fields, at the intersection of signal and
image processing, computer vision, and statistical machine learning. In
dictionary learning, the current methods of choice are arguably K-SVD and its
variants, which learn a ... | computer science |
4,395 | Configurable, Photorealistic Image Rendering and Ground Truth Synthesis
by Sampling Stochastic Grammars Representing Indoor Scenes | cs.CV | We propose the configurable rendering of massive quantities of photorealistic
images with ground truth for the purposes of training, benchmarking, and
diagnosing computer vision models. In contrast to the conventional
(crowd-sourced) manual labeling of ground truth for a relatively modest number
of RGB-D images capture... | computer science |
4,396 | Optic Disc and Cup Segmentation Methods for Glaucoma Detection with
Modification of U-Net Convolutional Neural Network | cs.CV | Glaucoma is the second leading cause of blindness all over the world, with
approximately 60 million cases reported worldwide in 2010. If undiagnosed in
time, glaucoma causes irreversible damage to the optic nerve leading to
blindness. The optic nerve head examination, which involves measurement of
cup-to-disc ratio, is... | computer science |
4,397 | Loss Max-Pooling for Semantic Image Segmentation | cs.CV | We introduce a novel loss max-pooling concept for handling imbalanced
training data distributions, applicable as alternative loss layer in the
context of deep neural networks for semantic image segmentation. Most
real-world semantic segmentation datasets exhibit long tail distributions with
few object categories compri... | computer science |
4,398 | Provable Self-Representation Based Outlier Detection in a Union of
Subspaces | cs.CV | Many computer vision tasks involve processing large amounts of data
contaminated by outliers, which need to be detected and rejected. While outlier
detection methods based on robust statistics have existed for decades, only
recently have methods based on sparse and low-rank representation been
developed along with guar... | computer science |
4,399 | Discriminative Bimodal Networks for Visual Localization and Detection
with Natural Language Queries | cs.CV | Associating image regions with text queries has been recently explored as a
new way to bridge visual and linguistic representations. A few pioneering
approaches have been proposed based on recurrent neural language models trained
generatively (e.g., generating captions), but achieving somewhat limited
localization accu... | computer science |
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