Xiaobo Jin
Impact in
- Bioengineering top 5%
- Analytical Chemistry and Sensors
-
- Multimodal Machine Learning Applications
Papers in
-
- Domain Adaptation and Few-Shot Learning 7
- Anomaly Detection Techniques and Applications 6
- Text and Document Classification Technologies 4
-
- Face and Expression Recognition 9
- Co-authors
- Guanggang Geng (13 shared papers)Guo-Sen Xie (9 shared papers)Kaizhu Huang (10 shared papers)Zheng Zhang (2 shared papers)Li Liu (1 shared paper)Yazhou Yao (1 shared paper)Jie Qin (1 shared paper)Fan Zhu (1 shared paper)
- Journals
- Cognitive Computation (4 papers)Computers & Security (3 papers)IEEE Access (2 papers)Pattern Recognition (2 papers)IEEE Transactions on Cognitive and Developmental Systems (1 paper)
- Partner nations
- ChinaUnited KingdomUnited Arab Emirates
In The Last Decade
Xiaobo Jin
44 papers receiving 847 citations
Peers
Comparison fields: 5 of 98
- Bioengineering 101
- Computer Vision and Pattern Recognition 306
- Artificial Intelligence 444
- Signal Processing 63
- Information Systems 104
Countries citing papers authored by Xiaobo Jin
This map shows the geographic impact of Xiaobo Jin'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 Xiaobo Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaobo Jin more than expected).
Fields of papers citing papers by Xiaobo Jin
This network shows the impact of papers produced by Xiaobo Jin. 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 Xiaobo Jin. The network helps show where Xiaobo Jin may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaobo Jin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 196 | |
| 2 | 2016 | 153 | |
| 3 | 2010 | 54 | |
| 4 | 2018 | 46 | |
| 5 | 2016 | 36 | |
| 6 | 2022 | 36 | |
| 7 | 2007 | 34 | |
| 8 | 2017 | 30 | |
| 9 | 2021 | 27 | |
| 10 | 2021 | 26 | |
| 11 | 2018 | 23 | |
| 12 | 2022 | 21 | |
| 13 | 2021 | 20 | |
| 14 | 2024 | 15 | |
| 15 | 2020 | 12 | |
| 16 | 2019 | 12 | |
| 17 | 2018 | 11 | |
| 18 | 2022 | 11 | |
| 19 | 2018 | 10 | |
| 20 | 2018 | 10 |
About Xiaobo Jin
Xiaobo Jin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Information Systems and Computer Networks and Communications, having authored 54 papers that have together received 876 indexed citations. Recurring topics across this work include Face and Expression Recognition (9 papers), Domain Adaptation and Few-Shot Learning (7 papers), Network Security and Intrusion Detection (6 papers), Anomaly Detection Techniques and Applications (6 papers), Spam and Phishing Detection (6 papers), Sparse and Compressive Sensing Techniques (5 papers), COVID-19 diagnosis using AI (4 papers) and Text and Document Classification Technologies (4 papers). The work is most often cited by research in Bioengineering (101 citations), Computer Vision and Pattern Recognition (306 citations), Artificial Intelligence (444 citations), Signal Processing (63 citations) and Information Systems (104 citations). Xiaobo Jin has collaborated with scholars based in China, United Kingdom and United Arab Emirates. Frequent co-authors include Guanggang Geng, Guo-Sen Xie, Kaizhu Huang, Zheng Zhang, Li Liu, Yazhou Yao, Jie Qin, Fan Zhu, Ling Shao and Yixiang Li. Their work appears in journals such as Cognitive Computation, Computers & Security, IEEE Access, Pattern Recognition and IEEE Transactions on Cognitive and Developmental Systems.
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.