Results 11 to 20 of about 215,679 (256)
, 2013 Recent developments in Carrillo et al. (2012) and Carrillo et al. (2013) introduced a novel regularization method for compressive imaging in the context of compressed sensing with coherent redundant dictionaries.
Carrillo, Rafael E. +2 more
core +4 more sources
Combinatorica, 2015 We prove that posets of bounded height whose cover graphs belong to a fixed class with bounded expansion have bounded dimension. Bounded expansion, introduced by Ne et il and Ossona de Mendez as a model for sparsity in graphs, is a property that is naturally satisfied by a wide range of graph classes, from graph structure theory (graphs excluding a ...
Joret, Gwenaël +2 more
openaire +5 more sources
Sparsity driven ultrasound imaging [PDF]
The Journal of the Acoustical Society of America, 2012 An image formation framework for ultrasound imaging from synthetic transducer arrays based on sparsity-driven regularization functionals using single-frequency Fourier domain data is proposed. The framework involves the use of a physics-based forward model of the ultrasound observation process, the formulation of image formation as the solution of an ...
Tüysüzoğlu, Ahmet +4 more
openaire +6 more sources
De-Biased Graphical Lasso for High-Frequency Data
Entropy, 2020 This paper develops a new statistical inference theory for the precision matrix of high-frequency data in a high-dimensional setting. The focus is not only on point estimation but also on interval estimation and hypothesis testing for entries of the ...
Yuta Koike
doaj +1 more source
Effect of sparsity-aware time–frequency analysis on dynamic hand gesture classification with radar micro-Doppler signatures [PDF]
, 2018 Dynamic hand gesture recognition is of great importance in human-computer interaction. In this study, the authors investigate the effect of sparsity-driven time-frequency analysis on hand gesture classification.
Fioranelli, Francesco +3 more
core +1 more source
Dynamic Sparsity Is Channel-Level Sparsity Learner
, 2023 Accepted by the 37th Conference on Neural Information Processing Systems (NeurIPS 2023)
Yin, Lu +9 more
openaire +2 more sources
Constructing Measures of Sparsity [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2022 This paper presents a rigorous but tractable study of sparsity. We postulate a definition of sparsity that is as broad as possible, so that it generates all the various measures that are useful in practice, but narrow enough that the fundamental properties of generalized sparsity still hold.
Mora-Jiménez, Inmaculada +4 more
openaire +3 more sources
Sparse Support Tensor Machine with Scaled Kernel Functions
Mathematics, 2023 As one of the supervised tensor learning methods, the support tensor machine (STM) for tensorial data classification is receiving increasing attention in machine learning and related applications, including remote sensing imaging, video processing, fault
Shuangyue Wang, Ziyan Luo
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Variational data assimilation via sparse regularisation [PDF]
Tellus: Series A, Dynamic Meteorology and Oceanography, 2014 This paper studies the role of sparse regularisation in a properly chosen basis for variational data assimilation (VDA) problems. Specifically, it focuses on data assimilation of noisy and down-sampled observations while the state variable of interest ...
Ardeshir M. Ebtehaj +3 more
doaj +1 more source
Blind Image Deblurring via a Novel Sparse Channel Prior
Mathematics, 2022 Blind image deblurring (BID) is a long-standing challenging problem in low-level image processing. To achieve visually pleasing results, it is of utmost importance to select good image priors. In this work, we develop the ratio of the dark channel prior (
Dayi Yang, Xiaojun Wu, Hefeng Yin
doaj +1 more source