Feature-Preserving Compression is a biomedical signal compression technique that belongs to the class of data reduction methods distinguished by its explicit prioritization of retaining diagnostically relevant physiological features during the compression process.
28
Publications
1.4K
Citations
85
Authors
50
Institutions
Publications per year
2017–2026
11
Publications
28
Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression
Yuchao Li, Shaohui Lin, Baochang Zhang et al. · 2019 · 142 citations
1–5 of 28
Authors
85
- FC
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- JS
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- XL
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1–5 of 85
Institutions
50
Argonne National Laboratory
Lemont, United States
3 h-index
11 publications
218 citations
Kyushu University
Fukuoka, Japan
2 h-index
2 publications
46 citations
University of California, Riverside
Riverside, United States
2 h-index
3 publications
71 citations
University of Michigan
Ann Arbor, United States
2 h-index
4 publications
630 citations
Kyoto University
Kyoto, Japan
2 h-index
2 publications
46 citations
University of California, Davis
Davis, United States
2 h-index
3 publications
117 citations
Peng Cheng Laboratory
Shenzhen, China
1 h-index
1 publications
142 citations
Université Paris 8
Paris, France
1 h-index
1 publications
18 citations
1–8 of 50
Venues
- Multimedia Tools and Applications
2 publications · 30 citations
2
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- Technometrics
2 publications · 315 citations
2
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- IEEE Transactions on Visualization and Computer Graphics
TVCG · 2 publications · 72 citations
2
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- Journal of Visual Communication and Image Representation
1 publications · 11 citations
1
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- IEEE Transactions on Image Processing
1 publications · 246 citations
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1–5