Fully Supervised Segmentation
Fully Supervised Segmentation is an image segmentation paradigm that belongs to the class of supervised learning methods and is distinguished by its reliance on densely annotated pixel-level labels for training, enabling the model to learn precise mappings from input images to their corresponding segmentation masks.
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466
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2017–2026
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Alexander M. Kirillov, Eric Mintun, Nikhila Ravi et al. · 2023 · 9.1K citations
Self-Supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentation
Yude Wang, Jie Zhang, Meina Kan et al. · 2020 · 750 citations
A Brief Survey on Semantic Segmentation with Deep Learning
Shijie Hao, Yuan Zhou, Yanrong Guo · Neurocomputing · 2020 · 589 citations
Micrograph segmentations for DDEVD
Alexander M. Kirillov, Eric Mintun, Nikhila Ravi et al. · arXiv (Cornell University) · 2023 · 543 citations · Full text
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175

Chinese Academy of Sciences
Beijing, China
7 h-index
23 publications
4.4K citations
University of Chinese Academy of Sciences
Beijing, China
5 h-index
15 publications
4.4K citations

Sun Yat-sen University
Guangzhou, China
5 h-index
10 publications
539 citations

University of British Columbia
Vancouver, Canada
4 h-index
6 publications
165 citations

University of Electronic Science and Technology of China
Chengdu, China
3 h-index
7 publications
369 citations
Fudan University
Shanghai, China
3 h-index
4 publications
373 citations
Karlsruhe Institute of Technology
Karlsruhe, Germany
3 h-index
9 publications
495 citations

Shenzhen University
Shenzhen, China
3 h-index
9 publications
288 citations
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Repository · 24 publications · 1.3K citations
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7 publications · 594 citations
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4 publications · 659 citations
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Conference · 3 publications · 109 citations
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Conference · 3 publications · 322 citations
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