Ju He
Impact in
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- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Multimodal Machine Learning Applications
- Visual Attention and Saliency Detection
- Artificial Intelligence top 10%
- Domain Adaptation and Few-Shot Learning
- Anomaly Detection Techniques and Applications
Papers in
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- Advanced Image and Video Retrieval Techniques 3
- Advanced Neural Network Applications 3
- Multimodal Machine Learning Applications 2
- Human Pose and Action Recognition 2
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- Domain Adaptation and Few-Shot Learning 4
- Anomaly Detection Techniques and Applications 2
- Co-authors
- Adam Kortylewski (4 shared papers)Yutong Bai (1 shared paper)Jie-Neng Chen (1 shared paper)Shuai Liu (1 shared paper)Changhu Wang (1 shared paper)Cheng Yang (1 shared paper)Alan Yuille (6 shared papers)Qing Liu (2 shared papers)
- Journals
- Computer Methods and Programs in Biomedicine (1 paper)Artificial Intelligence in Medicine (1 paper)Computers and Electronics in Agriculture (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (1 paper)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Ju He
11 papers receiving 442 citations
Ju He's Hit Papers
Peers
Comparison fields: 5 of 83
- Computer Vision and Pattern Recognition 310
- Artificial Intelligence 167
- Media Technology 29
- Small Animals 23
- Human-Computer Interaction 13
Countries citing papers authored by Ju He
This map shows the geographic impact of Ju He's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ju He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ju He more than expected).
Fields of papers citing papers by Ju He
This network shows the impact of papers produced by Ju He. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ju He. The network helps show where Ju He may publish in the future.
Co-authors
The 25 scholars most cited alongside Ju He, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | TransFG: A Transformer Architecture for Fine-Grained Recognition Hit paper breakdown → | 2022 | 270 |
| 2 | 2020 | 60 | |
| 3 | 2022 | 54 | |
| 4 | 2018 | 29 | |
| 5 | 2023 | 13 | |
| 6 | 2019 | 9 | |
| 7 | 2018 | 8 | |
| 8 | 2021 | 7 | |
| 9 | 2011 | 2 | |
| 10 | 2021 | 1 | |
| 11 | 2023 | 1 | |
| 12 | 2024 | 0 |
About Ju He
Ju He is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Small Animals and Animal Science and Zoology, having authored 12 papers that have together received 454 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (4 papers), Advanced Image and Video Retrieval Techniques (3 papers), Advanced Neural Network Applications (3 papers), Multimodal Machine Learning Applications (2 papers), Human Pose and Action Recognition (2 papers), Anomaly Detection Techniques and Applications (2 papers), Phytochemistry and Biological Activities (1 paper) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (310 citations), Artificial Intelligence (167 citations), Media Technology (29 citations), Small Animals (23 citations) and Human-Computer Interaction (13 citations). Ju He has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Adam Kortylewski, Yutong Bai, Jie-Neng Chen, Shuai Liu, Changhu Wang, Cheng Yang, Alan Yuille, Qing Liu, Lin Zhang and Qi She. Their work appears in journals such as Computer Methods and Programs in Biomedicine, Artificial Intelligence in Medicine, Computers and Electronics in Agriculture, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.