Results 11 to 20 of about 1,871,059 (300)
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
Sparse linear representation [PDF]
2009 IEEE International Symposium on Information Theory, 2009 5 pages, to appear in proc.
Halyun Jeong, Young-Han Kim 0001
openaire +3 more sources
Quantization of Sparse Representations [PDF]
2007 Data Compression Conference (DCC'07), 2007 Compressive sensing (CS) is a new signal acquisition technique for sparse and compressible signals. Rather than uniformly sampling the signal, CS computes inner products with randomized basis functions; the signal is then recovered by a convex optimization. Random CS measurements are universal in the sense that the same acquisition system is sufficient
Petros Boufounos, Richard G. Baraniuk
openaire +1 more source
Generating Images with Sparse Representations
CoRR, 2021 The high dimensionality of images presents architecture and sampling-efficiency challenges for likelihood-based generative models. Previous approaches such as VQ-VAE use deep autoencoders to obtain compact representations, which are more practical as inputs for likelihood-based models.
Charlie Nash +3 more
openaire +4 more sources
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
, 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, Foldiak, P
core +3 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
Multi-object tracking using sparse representation [PDF]
, 2013 Manuscript to ICASSP 2013International audienceRecently sparse representation has been successfully applied to single object tracking by observing the reconstruction error of candidate object with sparse representation. In practice, sparse representation
Lu, Weizhi +3 more
core +8 more sources