Multi-stage Data Processing
Multi-Stage Data Processing is a data orchestration framework that sequentially coordinates distinct, interdependent processing phases—such as ingestion, transformation, and analysis—to enable complex data workflows through structured, pipelined execution.
58
Publications
3.9K
Citations
310
Authors
159
Institutions
Publications per year
2017–2026
29
Parents
58
Hybrid Task Cascade for Instance Segmentation
Kai Chen, Jiangmiao Pang, Jiaqi Wang et al. · 2019 · 1.5K citations
Hybrid Task Cascade for Instance Segmentation
Kai Chen, Jiangmiao Pang, Jiaqi Wang et al. · arXiv (Cornell University) · 2019 · 175 citations · Full text
Pierre Bellec, Sébastien Lavoie-Courchesne, Phil Dickinson et al. · Frontiers in Neuroinformatics · 2012 · 122 citations · Full text
1–5 of 58
310
Hong Kong University of Science and Technology, Hong Kong SAR China
2 publications · 1.7K citations
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1–5 of 310
159

Chinese Academy of Sciences
Beijing, China
3 h-index
6 publications
231 citations
Argonne National Laboratory
Lemont, United States
3 h-index
9 publications
619 citations
University of Chinese Academy of Sciences
Beijing, China
2 h-index
4 publications
100 citations

Peking University
Beijing, China
2 h-index
3 publications
45 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
5 publications
153 citations
Arizona State University
Tempe, United States
2 h-index
4 publications
114 citations

King Abdulaziz University
Jeddah, Saudi Arabia
2 h-index
2 publications
79 citations
Institut National de Physique Nucléaire et de Physique des Particules
Paris, France
2 h-index
4 publications
122 citations
1–8 of 159
Repository · 3 publications · 223 citations
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2 publications · 41 citations
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1 publications · 33 citations
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Conference · 1 publications · 22 citations
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Conference · 1 publications · 12 citations
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