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A wavelet-integrated framework for feature extraction and background refinement in hyperspectral anomaly detection. [PDF]

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Sparse Recovery-Based Error Concealment

IEEE Transactions on Multimedia, 2017
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Akbari, Ali, Trocan, Maria, Granado, Bertrand   +2 more
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Accelerating Sparse Recovery by Reducing Chatter

SIAM Journal on Imaging Sciences, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Daskalakis, Emmanouil, Herrmann, Felix J., Kuske, Rachel   +2 more
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Joint Sparse Recovery Based on Variances

SIAM Journal on Scientific Computing, 2019
The authors consider a new weighted $\ell^1$-joint sparsity algorithm, where the weights depend on the calculated variance. Their construction is based on the fact that the supports of the signals to be recovered have similar supports, as well as the fact that the signals coefficients are reasonably distinct, which allow to infer that the elementwise ...
Ben Adcock, Anne Gelb, Guohui Song, Yi Sui   +3 more
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Sparse Recovery Approaches

2015
In this chapter, some concepts of sparse recovery approach from five branches are outlined. First, it outlines the convex relaxation method to recover the sparse signal which includes the linear programming method, second-order cone programming method, -homotopy method, and elastic net.
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Sparse Recovery from Inaccurate Saturated Measurements

Acta Applicandae Mathematicae, 2018
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Foucart, Simon, Li, Jiangyuan
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Sparse Recovery

2020
Vladimir Shikhman, David Müller
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Sparse Recovery

2018
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Cancer risk among World Trade Center rescue and recovery workers: A review

Ca-A Cancer Journal for Clinicians, 2022
Paolo Boffetta, Charles B Hall, Andrew C Todd   +2 more
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