Sparse Representation-based Classification
1개 벤치마크 · 논문 49편 · 이 태스크의 논문 보기 →
Benchmarks
SVHN
Most implemented
Linear Disentangled Representation Learning for Facial Actions
Associative Transformer
SparseFormer: Sparse Visual Recognition via Limited Latent Tokens
Multiplication fusion of sparse and collaborative-competitive representation for image classification
Deep Sparse Representation-based Classification
Papers
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 Classification