Patch-based Feature Extraction
Patch-Based Feature Extraction is a feature engineering method that involves partitioning an image into localized regions, or patches, to extract discriminative spatial patterns and textures specific to each subregion, thereby enabling fine-grained representation learning.
190
Publications
11.4K
Citations
707
Authors
306
Institutions
Publications per year
2017–2026
94
Parents
190
Patch-Based Convolutional Neural Network for Whole Slide Tissue Image Classification
Le Hou, Dimitris Samaras, Tahsin Kurç et al. · 2016 · 881 citations
Ran Margolin, Ayellet Tal, Lihi Zelnik‐Manor · 2013 · 525 citations
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306

Chinese Academy of Sciences
Beijing, China
9 h-index
25 publications
2K citations
University of Technology Sydney
Sydney, Australia
7 h-index
9 publications
1.8K citations

The University of Sydney
Sydney, Australia
6 h-index
12 publications
933 citations
Institute of Automation
Beijing, China
5 h-index
9 publications
497 citations
Nanyang Technological University
Singapore, Singapore
5 h-index
14 publications
708 citations

Xidian University
Xi'an, China
5 h-index
20 publications
1.2K citations

Huazhong University of Science and Technology
Wuhan, China
4 h-index
9 publications
269 citations
Singapore University of Social Sciences
Singapore, Singapore
4 h-index
4 publications
140 citations
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12 publications · 903 citations
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Repository · 9 publications · 246 citations
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6 publications · 157 citations
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5 publications · 217 citations
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TPAMI · 5 publications · 1.2K citations
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