Yupeng Chen
- Artificial Intelligence top 10%
- Metaheuristic Optimization Algorithms Research 3
- Evolutionary Algorithms and Applications 2
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- Face and Expression Recognition 3
- Video Surveillance and Tracking Methods 2
- Advanced Neural Network Applications 2
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- Data Management and Algorithms 1
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- Gene expression and cancer classification 2
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- Radiomics and Machine Learning in Medical Imaging 1
- Co-authors
- Qian XuXueting CuiJiahao FanGang WangYing LiJing-Ming GuoChaohuan HouYang-Geng Fu
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionComputational Theory and Mathematics
- Journals
- Expert Systems with Applications (2 papers)IEEE Access (2 papers)IEEE Internet of Things Journal (1 paper)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Yupeng Chen
12 papers receiving 313 citations
Peers
Comparison fields: 5 of 75
- Artificial Intelligence 187
- Computer Vision and Pattern Recognition 96
- Computational Theory and Mathematics 48
- Industrial and Manufacturing Engineering 15
- Signal Processing 15
Countries citing papers authored by Yupeng Chen
This map shows the geographic impact of Yupeng 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 Yupeng Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yupeng Chen more than expected).
Fields of papers citing papers by Yupeng Chen
This network shows the impact of papers produced by Yupeng 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 Yupeng Chen. The network helps show where Yupeng Chen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yupeng 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 | 2023 | 2 | |
| 2 | 2023 | 0 | |
| 3 | 2021 | 8 | |
| 4 | 2020 | 12 | |
| 5 | 2020 | 29 | |
| 6 | 2019 | 46 | |
| 7 | 2018 | 16 | |
| 8 | 2018 | 7 | |
| 9 | 2018 | 4 | |
| 10 | 2018 | 82 | |
| 11 | 2017 | 99 | |
| 12 | 2013 | 13 | |
| 13 | 1992 | 13 |
About Yupeng Chen
Yupeng Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 13 papers that have together received 331 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (3 papers), Face and Expression Recognition (3 papers), Evolutionary Algorithms and Applications (2 papers), Video Surveillance and Tracking Methods (2 papers), Advanced Neural Network Applications (2 papers), Gene expression and cancer classification (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and Data Management and Algorithms (1 paper). The work is most often cited by research in Artificial Intelligence (187 citations), Computer Vision and Pattern Recognition (96 citations) and Computational Theory and Mathematics (48 citations). Yupeng Chen has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Qian Xu, Xueting Cui, Jiahao Fan, Gang Wang, Ying Li, Gang Wang, Ying Li, Jing-Ming Guo, Ying Li and Chaohuan Hou. Their work appears in journals such as Expert Systems with Applications, IEEE Access and IEEE Internet of Things Journal.
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.