Multi-scale Context Modeling
Multi-Scale Context Modeling is a computational strategy in semantic segmentation that integrates contextual information across multiple spatial scales within an image, distinguishing itself by enabling the simultaneous capture of fine-grained local details and broader semantic dependencies to improve pixel-level classification accuracy.
63
Publications
4.3K
Citations
284
Authors
117
Institutions
Publications per year
2017–2026
54
Parents
63
MISSFormer: An Effective Medical Image Segmentation Transformer
Xiaohong Huang, Zhifang Deng, Dandan Li et al. · arXiv (Cornell University) · 2021 · 170 citations · Full text
ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias
Yufei Xu, Qiming Zhang, Jing Zhang et al. · arXiv (Cornell University) · 2021 · 156 citations · Full text
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117
Nanjing University of Posts and Telecommunications
Nanjing, China
3 h-index
11 publications
513 citations

Chinese Academy of Sciences
Beijing, China
3 h-index
10 publications
866 citations

Beihang University
Beijing, China
3 h-index
11 publications
928 citations
National University of Singapore
Singapore, Singapore
2 h-index
2 publications
128 citations

Zhejiang University
Hangzhou, China
2 h-index
12 publications
343 citations
University of Stuttgart
Stuttgart, Germany
2 h-index
2 publications
119 citations
Jilin University
Changchun, China
2 h-index
3 publications
270 citations
Tianjin University
Tianjin, China
2 h-index
9 publications
283 citations
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Repository · 8 publications · 470 citations
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3 publications · 127 citations
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2 publications · 50 citations
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2 publications · 112 citations
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Conference · 2 publications · 196 citations
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