Papers Sparse Representation-based Classification
“Sparse Representation-based Classification” 태그가 달린 논문 49편 · 필터 해제
Associative Transformer
Emerging from the pairwise attention in conventional Transformers, there is a growing interest in sparse attention mechanisms that align more closely with localized, contextual learning in the biological brain. Existing …
Artificial Global WorkspaceImage ClassificationInductive BiasRelational Reasoning+1SparseFormer: Sparse Visual Recognition via Limited Latent Tokens
Human visual recognition is a sparse process, where only a few salient visual cues are attended to rather than traversing every detail uniformly. However, most current vision networks follow a dense paradigm, processing …
Image ClassificationSparse Representation-based ClassificationVideo ClassificationMinimalistic Unsupervised Learning with the Sparse Manifold Transform
We describe a minimalistic and interpretable method for unsupervised learning, without resorting to data augmentation, hyperparameter tuning, or other engineering designs, that achieves performance close to the SOTA SSL …
Self-Supervised LearningSparse Representation-based ClassificationSpectral Graph ClusteringUnsupervised Image Classification+1A Personalized Zero-Shot ECG Arrhythmia Monitoring System: From Sparse Representation Based Domain Adaption to Energy Efficient Abnormal Beat Detection for Practical ECG Surveillance
This paper proposes a low-cost and highly accurate ECG-monitoring system intended for personalized early arrhythmia detection for wearable mobile sensors. Earlier supervised approaches for personalized ECG monitoring req…
Arrhythmia DetectionDictionary LearningDomain AdaptationECG Classification+2Stable and Compact Face Recognition via Unlabeled Data Driven Sparse Representation-Based Classification
Sparse representation-based classification (SRC) has attracted much attention by casting the recognition problem as simple linear regression problem. SRC methods, however, still is limited to enough labeled samples per c…
Face RecognitionSparse Representation-based ClassificationSparse Recovery via Bootstrapping: Collaborative or Independent?
Sparse regression problems have traditionally been solved using all available measurements simultaneously. However, this approach fails in challenging scenarios such as when the noise level is high or there are missing d…
Image ReconstructionregressionSparse Representation-based ClassificationMasked Face Image Classification with Sparse Representation based on Majority Voting Mechanism
Sparse approximation is the problem to find the sparsest linear combination for a signal from a redundant dictionary, which is widely applied in signal processing and compressed sensing. In this project, I manage to impl…
Classificationcompressed sensingGeneral Classificationimage-classification+2Automatic Identification of Epileptic Seizures from EEG Signals using Sparse Representation-based Classification
Identifying seizure activities in non-stationary electroencephalography (EEG) is a challenging task, since it is time-consuming, burdensome, and dependent on expensive human resources and subject to error and bias. A com…
Dictionary LearningEEGElectroencephalogram (EEG)Seizure Detection+3Multiplication fusion of sparse and collaborative-competitive representation for image classification
Representation based classification methods have become a hot research topic during the past few years, and the two most prominent approaches are sparse representation based classification (SRC) and collaborative represe…
ClassificationGeneral Classificationimage-classificationImage Classification+1Collaborative representation-based robust face recognition by discriminative low-rank representation
We consider the problem of robust face recognition in which both the training and test samples might be corrupted because of disguise and occlusion. Performance of conventional subspace learning methods and recently prop…
Face RecognitionGeneral ClassificationRobust Face RecognitionSparse Representation-based ClassificationNon-intrusive Load Monitoring via Multi-label Sparse Representation based Classification
This work follows the approach of multi-label classification for non-intrusive load monitoring (NILM). We modify the popular sparse representation based classification (SRC) approach (developed for single label classific…
ClassificationGeneral ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+2Learning a Representation with the Block-Diagonal Structure for Pattern Classification
Sparse-representation-based classification (SRC) has been widely studied and developed for various practical signal classification applications. However, the performance of a SRC-based method is degraded when both the tr…
BenchmarkingClassificationGeneral ClassificationSparse Representation-based ClassificationA Paired Sparse Representation Model for Robust Face Recognition from a Single Sample
Sparse representation-based classification (SRC) has been shown to achieve a high level of accuracy in face recognition (FR). However, matching faces captured in unconstrained video against a gallery with a single refere…
Face RecognitionRobust Face RecognitionSparse Representation-based ClassificationDeep Sparse Representation-based Classification
We present a transductive deep learning-based formulation for the sparse representation-based classification (SRC) method. The proposed network consists of a convolutional autoencoder along with a fully-connected layer. …
ClassificationDecoderGeneral ClassificationImage Classification+2A Fast Dictionary Learning Method for Coupled Feature Space Learning
In this letter, we propose a novel computationally efficient coupled dictionary learning method that enforces pairwise correlation between the atoms of dictionaries learned to represent the underlying feature spaces of t…
Dictionary LearningGeneral ClassificationSparse Representation-based ClassificationInverse Projection Representation and Category Contribution Rate for Robust Tumor Recognition
Sparse representation based classification (SRC) methods have achieved remarkable results. SRC, however, still suffer from requiring enough training samples, insufficient use of test samples and instability of representa…
ClassificationGeneral ClassificationSparse Representation-based ClassificationThe Use of Mutual Coherence to Prove $\ell^1/\ell^0$-Equivalence in Classification Problems
We consider the decomposition of a signal over an overcomplete set of vectors. Minimization of the $\ell^1$-norm of the coefficient vector can often retrieve the sparsest solution (so-called "$\ell^1/\ell^0$-equivalence"…
compressed sensingGeneral ClassificationSparse Representation-based ClassificationClassifying Multi-channel UWB SAR Imagery via Tensor Sparsity Learning Techniques
Using low-frequency (UHF to L-band) ultra-wideband (UWB) synthetic aperture radar (SAR) technology for detecting buried and obscured targets, e.g. bomb or mine, has been successfully demonstrated recently. Despite promis…
Dictionary LearningGeneral ClassificationSparse Representation-based ClassificationAn Integrated Inverse Space Sparse Representation Framework for Tumor Classification
Microarray gene expression data-based tumor classification is an active and challenging issue. In this paper, an integrated tumor classification framework is presented, which aims to exploit information in existing avail…
ClassificationGeneral ClassificationSparse Representation-based ClassificationSpecificityDeep Network for Simultaneous Decomposition and Classification in UWB-SAR Imagery
Classifying buried and obscured targets of interest from other natural and manmade clutter objects in the scene is an important problem for the U.S. Army. Targets of interest are often represented by signals captured usi…
ClassificationDenoisingGeneral ClassificationSparse Representation-based Classification