Results 21 to 30 of about 523,433 (260)
Deep Sparse Representation-Based Classification [PDF]
IEEE Signal Processing Letters, 2019 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. The role of the autoencoder network is to learn robust deep features for classification. On the other hand, the fully-connected layer,
Mahdi Abavisani, Vishal M. Patel
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Local Connectivity Enhanced Sparse Representation
IEEE Access, 2020 During the past two decades, the subspace clustering problem has attracted much attention. Since the data set in real-world problems usually contains a lot of categories, it seems that the large subspace number (LSN) subspace clustering has great ...
Kewei Tang +6 more
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Fast Parallel Randomized Algorithm for Nonnegative Matrix Factorization with KL Divergence for Large Sparse Datasets [PDF]
, 2016 Nonnegative Matrix Factorization (NMF) with Kullback-Leibler Divergence (NMF-KL) is one of the most significant NMF problems and equivalent to Probabilistic Latent Semantic Indexing (PLSI), which has been successfully applied in many applications.
Ho, Tu Bao, Nguyen, Duy Khuong
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Sparse Representations of Random Signals [PDF]
Mathematical Methods in the Applied Sciences, 2021 Sparse (fast) representations of deterministic signals have been well studied. Among other types there exists one called adaptive Fourier decomposition (AFD) for functions in analytic Hardy spaces. Through the Hardy space decomposition of the $L^2$ space the AFD algorithm also gives rise to sparse representations of signals of finite energy.
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Sparse representation of salient regions for no-reference image quality assessment
International Journal of Advanced Robotic Systems, 2016 This paper introduces an efficient feature learning framework via sparse coding for no-reference image quality assessment. The important part of the proposed framework is based on sparse feature extraction from a sparse representation matrix, which is ...
Tianpeng Feng +5 more
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A weighted block cooperative sparse representation algorithm based on visual saliency dictionary
CAAI Transactions on Intelligence Technology, 2023 Unconstrained face images are interfered by many factors such as illumination, posture, expression, occlusion, age, accessories and so on, resulting in the randomness of the noise pollution implied in the original samples.
Rui Chen +4 more
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Learning Sparse Representations of Depth [PDF]
IEEE Journal of Selected Topics in Signal Processing, 2011 This paper introduces a new method for learning and inferring sparse representations of depth (disparity) maps. The proposed algorithm relaxes the usual assumption of the stationary noise model in sparse coding. This enables learning from data corrupted with spatially varying noise or uncertainty, typically obtained by laser range scanners or ...
Tosic, Ivana +2 more
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Robust Face Recognition Via Gabor Feature and Sparse Representation
ITM Web of Conferences, 2016 Sparse representation based on compressed sensing theory has been widely used in the field of face recognition, and has achieved good recognition results.
Hao Yu-Juan, Zhang Li-Quan
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Compressive Sampling for Remote Control Systems [PDF]
, 2012 In remote control, efficient compression or representation of control signals is essential to send them through rate-limited channels. For this purpose, we propose an approach of sparse control signal representation using the compressive sampling ...
Hayashi, Kazunori +2 more
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Image compression-encryption method based on two-dimensional sparse recovery and chaotic system
Scientific Reports, 2021 In this paper, we propose an image compression-encryption method based on two-dimensional (2D) sparse representation and chaotic system. In the first step of this method, the input image is extended in a transform domain to obtain a sparse representation.
Aboozar Ghaffari
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