https://github.com/aim-uofa/partially-labelled
Learning to segment multi-organ and tumorsfrom multiple partially labeled datasets
Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: arxiv.org -
○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (3.7%) to scientific vocabulary
Repository
Learning to segment multi-organ and tumorsfrom multiple partially labeled datasets
Basic Info
- Host: GitHub
- Owner: aim-uofa
- License: gpl-3.0
- Default Branch: main
- Size: 15.6 KB
Statistics
- Stars: 19
- Watchers: 5
- Forks: 2
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
Learning to segment multi-organ and tumorsfrom multiple partially labeled datasets
Paper can be found here: https://arxiv.org/abs/2011.10217
The code and models are now hosted at: https://github.com/jianpengz/DoDNet
Please cite our paper if find the code useful:
bibtex
inproceedings{DoDNet2021CVPR,
title = {{DoDNet:} Learning to segment multi-organ and tumors from multiple partially labeled datasets},
author= {Jianpeng Zhang and Yutong Xie and Yong Xia and Chunhua Shen},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2021)},
year=2021,
}
Owner
- Name: Advanced Intelligent Machines (AIM)
- Login: aim-uofa
- Kind: organization
- Location: China
- Repositories: 23
- Profile: https://github.com/aim-uofa
A research team at Zhejiang University, focusing on Computer Vision and broad AI research ...
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- Average comments per issue: 3.0
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Top Authors
Issue Authors
- GuobinZhangTJU (1)