Results 11 to 20 of about 114,572 (313)
Sparse Representation Based Projections [PDF]
Procedings of the British Machine Vision Conference 2011, 2011 In dimensionality reduction most methods aim at preserving one or a few properties of the original space in the resulting embedding. As our results show, preserving the sparse representation of the signals from the original space in the (lower) dimensional projected space is beneficial for several benchmarks (faces, traffic signs, and handwritten ...
Radu Timofte, Luc Van Gool
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IEEE Access, 2020 Multitask sparse representation method improves the detection performance by constructing multiple associated sub-sparse representation tasks and jointly learning multiple sub-sparse representation tasks, and this method can make use of the spectral ...
Xianfeng Ou +6 more
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Memory Model for Morphological Semantics of Visual Stimuli Using Sparse Distributed Representation
Applied Sciences, 2021 Recent achievements on CNN (convolutional neural networks) and DNN (deep neural networks) researches provide a lot of practical applications on computer vision area.
Kyuchang Kang, Changseok Bae
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Sparse image representation with epitomes [PDF]
CVPR 2011, 2011 Computer Vision and Pattern Recognition, Colorado Springs : United States (2011)
Benoît, Louise +3 more
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Improved sparse representation using adaptive spatial support for effective target detection in hyperspectral imagery [PDF]
, 2013 With increasing applications of hyperspectral imagery (HSI) in agriculture, mineralogy, military, and other fields, one of the fundamental tasks is accurate detection of the target of interest.
Li, Xiaohui +3 more
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A novel sparse representation algorithm for AIS real-time signals
EURASIP Journal on Wireless Communications and Networking, 2018 Sparse representation of signals based on a redundant dictionary is a new signal representation theory. Recent research activities in this field have concentrated mainly on the study of dictionary design and sparse decomposition algorithms.
Shuaiheng Huai, Shufang Zhang
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Voxel selection in fMRI data analysis based on sparse representation [PDF]
, 2009 Multivariate pattern analysis approaches toward detection of brain regions from fMRI data have been gaining attention recently. In this study, we introduce an iterative sparse-representation-based algorithm for detection of voxels in functional MRI (fMRI)
Namburi, Praneeth +5 more
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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.
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Multiple Graph Adaptive Regularized Semi-Supervised Nonnegative Matrix Factorization with Sparse Constraint for Data Representation [PDF]
, 2022 Multiple graph and semi-supervision techniques have been successfully introduced into the nonnegative matrix factorization (NMF) model for taking full advantage of the manifold structure and priori information of data to capture excellent low-dimensional
Yi Wang +11 more
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