Contextual Dependencies
Contextual Dependencies is a formal model in context diagramming that specifies the external relationships and influences between a system and its surrounding entities, distinguishing itself by capturing how environmental factors directly constrain or enable system behavior.
279
Publications
27.8K
Citations
937
Authors
350
Institutions
Publications per year
2017–2026
170
Parents
279
Dual Attention Network for Scene Segmentation
Jun Fu, Jing Liu, Haijie Tian et al. · 2019 · 6.8K citations
Conformer: Convolution-augmented Transformer for Speech Recognition
Anmol Gulati, James Qin, Chung‐Cheng Chiu et al. · 2020 · 2.7K citations
Rotate to Attend: Convolutional Triplet Attention Module
Diganta Misra, Trikay Nalamada, Ajay Uppili Arasanipalai et al. · 2021 · 1.1K citations
MA-Net: A Multi-Scale Attention Network for Liver and Tumor Segmentation
Tongle Fan, Guanglei Wang, Yan Li et al. · IEEE Access · 2020 · 468 citations · Full text
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350

Chinese Academy of Sciences
Beijing, China
11 h-index
42 publications
38.1K citations
University of Chinese Academy of Sciences
Beijing, China
9 h-index
27 publications
16.5K citations
Nanyang Technological University
Singapore, Singapore
8 h-index
20 publications
1.9K citations

Beihang University
Beijing, China
7 h-index
24 publications
1.3K citations

Zhejiang University
Hangzhou, China
7 h-index
21 publications
1.4K citations
Massachusetts Institute of Technology
Cambridge, United States
6 h-index
8 publications
578 citations

University of Electronic Science and Technology of China
Chengdu, China
6 h-index
12 publications
1K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
5 h-index
5 publications
402 citations
1–8 of 350
Repository · 25 publications · 1.2K citations
15
h-index
11 publications · 1.5K citations
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Conference · 7 publications · 669 citations
7
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6 publications · 635 citations
6
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6 publications · 248 citations
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