Results 21 to 30 of about 528,580 (282)
Subspace-Sparse Representation
CoRR, 2015 15 pages, 3 figures, previous version published in ICML ...
Chong You, René Vidal
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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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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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3-D Sparse Representations [PDF]
, 2014 In this chapter we review a variety of 3D sparse representations developed in recent years and adapted to different kinds of 3D signals. In particular, we describe 3D wavelets, ridgelets, beamlets and curvelets. We also present very recent 3D sparse representations on the 3D ball adapted to 3D signal naturally observed in spherical coordinates ...
Lanusse, François +3 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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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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Sparseness and Expansion in Sensory Representations [PDF]
Neuron, 2014 In several sensory pathways, input stimuli project to sparsely active downstream populations that have more neurons than incoming axons. Here, we address the computational benefits of expansion and sparseness for clustered inputs, where different clusters represent behaviorally distinct stimuli and intracluster variability represents sensory or ...
Babadi, Baktash, Sompolinsky, Haim
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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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Application of Compressive Sensing Theory for the Reconstruction of Signals in Plastic Scintillators [PDF]
, 2013 Compressive Sensing theory says that it is possible to reconstruct a measured signal if an enough sparse representation of this signal exists in comparison to the number of random measurements.
Bednarski, T. +24 more
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