Bin Chen
- Media Technology top 5%
- Image Processing Techniques and Applications 7
- Advanced Image Fusion Techniques 5
- Atmospheric Science top 10%
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- Video Surveillance and Tracking Methods 7
- Advanced Neural Network Applications 6
- Image Retrieval and Classification Techniques 5
- Image and Signal Denoising Methods 5
- Condensed Matter Physics top 10%
- Global and Planetary Change top 10%
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- Industrial Vision Systems and Defect Detection 6
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- Robotics and Sensor-Based Localization 5
- Co-authors
- J. Ilja SiepmannDavid W. MessingerHsi-Jian LeeZengshun ChenKai WangCongjun WuXi DaiZhao-Bin Su
- Journals
- Neurocomputing (3 papers)IEEE Access (2 papers)The Journal of Physical Chemistry B (2 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Bin Chen
102 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 146
- Media Technology 112
- Atmospheric Science 221
- Computer Vision and Pattern Recognition 225
- Condensed Matter Physics 88
- Global and Planetary Change 113
Countries citing papers authored by Bin Chen
This map shows the geographic impact of Bin Chen'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 Bin Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Chen more than expected).
Fields of papers citing papers by Bin Chen
This network shows the impact of papers produced by Bin Chen. 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 Bin Chen. The network helps show where Bin Chen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bin Chen, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 2 | |
| 10 | 2023 | 18 | |
| 11 | 2023 | 2 | |
| 12 | 2023 | 1 | |
| 13 | 2022 | 3 | |
| 14 | 2021 | 9 | |
| 15 | 2021 | 1 | |
| 16 | 2019 | 1 | |
| 17 | 2018 | 27 | |
| 18 | Study on online outlier detection method based on principal component analysis and Bayesian classification | 2013 | 1 |
| 19 | Investigation on the Interaction of Tetrabutyltin Compound and Humic Acids by Spectroscopy | 2010 | 1 |
| 20 | Computer recognition system of plant leaf--shape | 2005 | 1 |
About Bin Chen
Bin Chen is a scholar working on Computer Vision and Pattern Recognition, Computational Mathematics and Media Technology, having authored 114 papers that have together received 1.4k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (7 papers), Image Processing Techniques and Applications (7 papers), Advanced Neural Network Applications (6 papers), Industrial Vision Systems and Defect Detection (6 papers), Image Retrieval and Classification Techniques (5 papers), Image and Signal Denoising Methods (5 papers), Robotics and Sensor-Based Localization (5 papers) and Advanced Image Fusion Techniques (5 papers). The work is most often cited by research in Media Technology (112 citations), Atmospheric Science (221 citations) and Computer Vision and Pattern Recognition (225 citations). Bin Chen has collaborated with scholars based in China, United States and Japan. Frequent co-authors include J. Ilja Siepmann, David W. Messinger, Hsi-Jian Lee, Zengshun Chen, Kai Wang, Congjun Wu, Xi Dai, Zhao-Bin Su, Yue Yu and Aihao Ding. Their work appears in journals such as Neurocomputing, IEEE Access, The Journal of Physical Chemistry B, Scientific Reports and Cell Death Discovery.
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.