Annotation-efficient Segmentation
Annotation-Efficient Segmentation is a semantic segmentation paradigm that reduces the reliance on extensively annotated training data by leveraging techniques such as weak supervision, few-shot learning, or active labeling to achieve high segmentation performance with minimal human-labeled supervision.
54
Publications
2.6K
Citations
311
Authors
151
Institutions
Publications per year
2017–2026
53
Parents
54
Segment Anything for Microscopy
Anwai Archit, Luca Freckmann, Sushmita Nair et al. · Nature Methods · 2025 · 186 citations · Full text
Video Polyp Segmentation: A Deep Learning Perspective
Ge-Peng Ji, Guobao Xiao, Yu-Cheng Chou et al. · Machine Intelligence Research · 2022 · 161 citations · Full text
Polyp-SAM: transfer SAM for polyp segmentation
Mingzhe Hu, Xiaofeng Yang · 2024 · 92 citations
1–5 of 54
311
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University of Electronic Science and Technology of China, China
2 publications · 111 citations
2
h-index
1–5 of 311
151
Shanghai Artificial Intelligence Laboratory
Shanghai, China
3 h-index
8 publications
364 citations

University of Electronic Science and Technology of China
Chengdu, China
3 h-index
16 publications
807 citations
Shenzhen Institutes of Advanced Technology
Shenzhen, China
2 h-index
8 publications
137 citations

Shanghai Jiao Tong University
Shanghai, China
2 h-index
11 publications
243 citations
German Research Centre for Artificial Intelligence
Kaiserslautern, Germany
2 h-index
9 publications
1.2K citations

University of Rochester
Rochester, United States
2 h-index
3 publications
135 citations
Henan Provincial People's Hospital
Zhengzhou, China
2 h-index
4 publications
451 citations
Stanford University
Stanford, United States
2 h-index
3 publications
857 citations
1–8 of 151
Repository · 11 publications · 319 citations
11
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9 publications · 327 citations
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2 publications · 44 citations
2
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AI · 1 publications · 16 citations
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Repository · 1 publications · 67 citations
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