Results 11 to 20 of about 1,813,028 (298)
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
core +4 more sources
, 2008 The(frequently updated) original version is avalable at http://www.scholarpedia.org/article/Sparse_codingMammalian brains consist of billions of neurons, each capable of independent electrical activity.
Endres, D M +3 more
core +3 more sources
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
doaj +1 more source
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 ...
Ivana Tosic +2 more
openaire +2 more sources
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
openaire +2 more sources
Sparse image representation with epitomes [PDF]
CVPR 2011, 2011 Computer Vision and Pattern Recognition, Colorado Springs : United States (2011)
Benoît, Louise +3 more
openaire +5 more sources
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
core +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source