Results 21 to 30 of about 1,871,059 (300)
Hyperspectral Anomaly Detection via Sparse Representation and Collaborative Representation
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Sparse representation (SR)-based approaches and collaborative representation (CR)-based methods are proved to be effective to detect the anomalies in a hyperspectral image (HSI).
Sheng Lin +5 more
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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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Subspace-Sparse Representation
CoRR, 2015 15 pages, 3 figures, previous version published in ICML ...
Chong You, René Vidal
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Sparse representation of astronomical images [PDF]
Journal of the Optical Society of America A, 2013 Sparse representation of astronomical images is discussed. It is shown that a significant gain in sparsity is achieved when particular mixed dictionaries are used for approximating these types of images with greedy selection strategies. Experiments are conducted to confirm: i)Effectiveness at producing sparse representations.
Laura Rebollo-Neira, James Bowley
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Explicit Object Representation by Sparse Neural Codes [PDF]
, 2008 Neurons have been identified in the human medial temporal lobe (MTL) that display a strong selectivity for only a few stimuli (such as familiar individuals or landmark buildings) out of perhaps 100 presented to the test subject.
Waydo, Stephen J.
core +1 more source
Spiralet Sparse Representation
CoRR, 2014 10 pages, Working Paper Number: WP-RFM-14 ...
Reza Farrahi Moghaddam, Mohamed Cheriet
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Sparse representations in audio & music: from coding to source separation [PDF]
, 2010 —Sparse representations have proved a powerful toolin the analysis and processing of audio signals and already lieat the heart of popular coding standards such as MP3 andDolby AAC.
Davies, ME +15 more
core +1 more source
Joint Sparse Representation-based Single Image Super-Resolution for Remote Sensing Applications
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Sparse representation-based single image super-resolution (SISR) methods use a coupled overcomplete dictionary trained from high-resolution images/image patches.
Bhabesh Deka +3 more
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Bayesian Orthogonal Component Analysis for Sparse Representation [PDF]
, 2010 This paper addresses the problem of identifying a lower dimensional space where observed data can be sparsely represented. This undercomplete dictionary learning task can be formulated as a blind separation problem of sparse sources linearly mixed with ...
Nicolas Dobigeon +3 more
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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
doaj +1 more source