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Published in 2023 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2023.3278026
Abstract: Sparsity-regularized linear inverse problem has served as the base in many disciplines, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, medical imaging, and so forth. The iterative hard thresholding algorithm…
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Keywords:
linear inverse;
sparsity regularized;
regularized linear;
method ... See more keywords
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Published in 2025 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2025.3574446
Abstract: The sparsity-regularized linear inverse problem has been widely used in many fields, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, medical imaging, etc. This method offers greater flexibility in solving…
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Keywords:
sparse regularization;
regularized linear;
sparsity regularized;
linear inverse ... See more keywords
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2
Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3267070
Abstract: The past decade has witnessed the rapid development of deep learning techniques, especially for large-scale and complex datasets. However, it is still a noteworthy problem in dealing with unsupervised hyperspectral image (HSI) segmentation since inefficiency…
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Keywords:
linear embedding;
deep spectral;
regularized linear;
spectral clustering ... See more keywords
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Published in 2025 at "Journal of Climate"
DOI: 10.1175/jcli-d-25-0145.1
Abstract: How the spatially varying temperature field affects global radiation (the “pattern effect”) is crucial to understanding how sensitive Earth’s temperature is to anthropogenic forcing. Here we estimate this phenomenon by forming temperature sensitivity maps using…
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Keywords:
regularized linear;
using regularized;
pattern effect;
linear regression ... See more keywords