Results 31 to 40 of about 114,572 (313)
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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Identification of Matrices Having a Sparse Representation [PDF]
, 2008 We consider the problem of recovering a matrix from its action on a known vector in the setting where the matrix can be represented efficiently in a known matrix dictionary.
Pfander, Goetz E. +6 more
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Sparse‐Dyn: Sparse dynamic graph multirepresentation learning via event‐based sparse temporal attention network [PDF]
, 2022 Dynamic graph neural networks (DGNNs) have been widely used in modeling and representation learning of graph structure data. Current dynamic representation learning focuses on either discrete learning which results in temporal information loss, or ...
Liu, Chao +15 more
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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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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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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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The cosparse analysis model and algorithms [PDF]
, 2013 After a decade of extensive study of the sparse representation synthesis model, we can safely say that this is a mature and stable field, with clear theoretical foundations, and appealing applications.
Gribonval, Rémi +8 more
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Image compression-encryption method based on two-dimensional sparse recovery and chaotic system
Scientific Reports, 2021 In this paper, we propose an image compression-encryption method based on two-dimensional (2D) sparse representation and chaotic system. In the first step of this method, the input image is extended in a transform domain to obtain a sparse representation.
Aboozar Ghaffari
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Sparse time-frequency representations [PDF]
Proceedings of the National Academy of Sciences, 2006 Auditory neurons preserve exquisite temporal information about sound features, but we do not know how the brain uses this information to process the rapidly changing sounds of the natural world. Simple arguments for effective use of temporal information led us to consider the reassignment class of time-frequency representations as ...
Gardner, Timothy J. +1 more
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Shock and Vibration, 2020 The feature extraction of wheelset-bearing fault is important for the safety service of high-speed train. In recent years, sparse representation is gradually applied to the fault diagnosis of wheelset-bearing.
Zhan Xing +3 more
doaj +1 more source