Chenye Guan
Impact in
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- Advanced Neural Network Applications
- Advanced Vision and Imaging
- Video Surveillance and Tracking Methods
- Optical measurement and interference techniques
- Geology top 5%
Papers in
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- Advanced Vision and Imaging 4
- Advanced Neural Network Applications 4
- Visual Attention and Saliency Detection 1
- Optical measurement and interference techniques 1
- Advanced Image and Video Retrieval Techniques 1
- Video Surveillance and Tracking Methods 1
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- Robotics and Sensor-Based Localization 2
- Co-authors
- Ruigang Yang (7 shared papers)Dingfu Zhou (3 shared papers)Junbo Yin (2 shared papers)Xibin Song (2 shared papers)Yuchao Dai (2 shared papers)Peng Wang (3 shared papers)Jin Fang (3 shared papers)Xinjing Cheng (2 shared papers)
- Journals
- Oxford University Research Archive (ORA) (University of Oxford) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)ANU Open Research (Australian National University) (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Chenye Guan
7 papers receiving 743 citations
Chenye Guan's Hit Papers
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 597
- Geology 72
- Media Technology 110
- Instrumentation 35
- Aerospace Engineering 238
Countries citing papers authored by Chenye Guan
This map shows the geographic impact of Chenye Guan'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 Chenye Guan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chenye Guan more than expected).
Fields of papers citing papers by Chenye Guan
This network shows the impact of papers produced by Chenye Guan. 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 Chenye Guan. The network helps show where Chenye Guan may publish in the future.
Co-authors
The 24 scholars most cited alongside Chenye Guan, 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 | IoU Loss for 2D/3D Object Detection Hit paper breakdown → | 2019 | 314 |
| 2 | 2020 | 157 | |
| 3 | 2019 | 112 | |
| 4 | 2020 | 105 | |
| 5 | 2020 | 38 | |
| 6 | 2020 | 22 | |
| 7 | 2020 | 8 |
About Chenye Guan
Chenye Guan is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Computational Mechanics, Environmental Engineering and Infectious Diseases, having authored 7 papers that have together received 756 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (4 papers), Advanced Neural Network Applications (4 papers), Robotics and Sensor-Based Localization (2 papers), 3D Shape Modeling and Analysis (1 paper), Visual Attention and Saliency Detection (1 paper), Optical measurement and interference techniques (1 paper), Advanced Image and Video Retrieval Techniques (1 paper) and Video Surveillance and Tracking Methods (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (597 citations), Geology (72 citations), Media Technology (110 citations), Instrumentation (35 citations) and Aerospace Engineering (238 citations). Chenye Guan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Ruigang Yang, Dingfu Zhou, Junbo Yin, Xibin Song, Yuchao Dai, Peng Wang, Jin Fang, Xinjing Cheng, Jianbing Shen and Hao Su. Their work appears in journals such as Oxford University Research Archive (ORA) (University of Oxford), Proceedings of the AAAI Conference on Artificial Intelligence and ANU Open Research (Australian National University).
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.