Results 61 to 70 of about 114,572 (313)
Hyperspectral Image Denoising via Nonlocal Spectral Sparse Subspace Representation
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Hyperspectral image (HSI) denoising based on nonlocal subspace representation has attracted a lot of attention recently. However, most of the existing works mainly focus on refining the representation coefficient images (RCIs) using certain nonlocal ...
Hailin Wang +5 more
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Sparse Representations of Random Signals [PDF]
Mathematical Methods in the Applied Sciences, 2021 Sparse (fast) representations of deterministic signals have been well studied. Among other types there exists one called adaptive Fourier decomposition (AFD) for functions in analytic Hardy spaces. Through the Hardy space decomposition of the $L^2$ space the AFD algorithm also gives rise to sparse representations of signals of finite energy.
openaire +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Sparse Representation and Collaborative Representation? Both Help Image Classification
IEEE Access, 2019 Image classification has attracted more and more attention. During the past decades, image classification has shown growing interest in representation-based classification methods, such as sparse representation-based classification and collaborative ...
Wen-Yang Xie +4 more
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Remote Sensing, 2020 In recent years, with the development of compressed sensing theory, sparse representation methods have been concerned by many researchers. Sparse representation can approximate the original image information with less space storage. Sparse representation
Xiaobin Zhao +4 more
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Sparse representation of Gravitational Sound [PDF]
Journal of Sound and Vibration, 2018 Gravitational Sound clips produced by the Laser Interferometer Gravitational-Wave Observatory (LIGO) and the Massachusetts Institute of Technology (MIT) are considered within the particular context of data reduction. It is shown that these types of signals can be approximated at high quality using much less elementary components than those required ...
Rebollo Neira, Laura +1 more
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Unlearning via Sparse Representations
CoRR, 2023 Machine \emph{unlearning}, which involves erasing knowledge about a \emph{forget set} from a trained model, can prove to be costly and infeasible by existing techniques. We propose a nearly compute-free zero-shot unlearning technique based on a discrete representational bottleneck. We show that the proposed technique efficiently unlearns the forget set
Vedant Shah +7 more
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Sparse Matrix Representation for Web Opinions [PDF]
, 2012 Due to the advancement of Web 2.0 technologies, a large volume of Web opinions is available on social media sites such as Web forums and Weblogs. These technologies provide a platform for Internet users around the world to communicate with each other and
Dileep kumar B R +1 more
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Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Combinatorial Regression and Improved Basis Pursuit for Sparse Estimation [PDF]
, 2012 Sparse representations accurately model many real-world data sets. Some form of sparsity is conceivable in almost every practical application, from image and video processing, to spectral sensing in radar detection, to bio-computation and genomic signal ...
Khajehnejad, M. Amin
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