Bo Tang
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- Advanced Neural Network Applications 7
- Artificial Intelligence top 1%
- Anomaly Detection Techniques and Applications 8
- Domain Adaptation and Few-Shot Learning 7
- Automotive Engineering top 2%
- Autonomous Vehicle Technology and Safety 11
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- IoT and Edge/Fog Computing 7
- Media Technology top 1%
- Remote-Sensing Image Classification 10
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- Indoor and Outdoor Localization Technologies 9
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- Cloud Data Security Solutions 7
- Co-authors
- Haibo HeSteven KayLong ChenXuemin HuQing YangTao WeiZhen ChenGerald Hefferman
- Journals
- SHILAP Revista de lepidopterología (1 paper)Chemistry of Materials (1 paper)Proceedings of the IEEE (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Bo Tang
120 papers receiving 3.3k citations
Peers
Comparison fields: 5 of 146
- Computer Vision and Pattern Recognition 927
- Artificial Intelligence 1.3k
- Automotive Engineering 423
- Computer Networks and Communications 716
- Media Technology 252
Countries citing papers authored by Bo Tang
This map shows the geographic impact of Bo Tang'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 Bo Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bo Tang more than expected).
Fields of papers citing papers by Bo Tang
This network shows the impact of papers produced by Bo Tang. 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 Bo Tang. The network helps show where Bo Tang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bo Tang, 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 | 2023 | 51 | |
| 6 | 2023 | 24 | |
| 7 | 2023 | 15 | |
| 8 | 2023 | 21 | |
| 9 | 2022 | 25 | |
| 10 | 2022 | 14 | |
| 11 | 2021 | 30 | |
| 12 | 2021 | 20 | |
| 13 | 2021 | 9 | |
| 14 | 2021 | 87 | |
| 15 | 2020 | 84 | |
| 16 | 2020 | 13 | |
| 17 | 2020 | 27 | |
| 18 | 2019 | 1 | |
| 19 | 2019 | 47 | |
| 20 | 2019 | 13 |
About Bo Tang
Bo Tang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 129 papers that have together received 3.5k indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (11 papers), Remote-Sensing Image Classification (10 papers), Indoor and Outdoor Localization Technologies (9 papers), Anomaly Detection Techniques and Applications (8 papers), Cloud Data Security Solutions (7 papers), IoT and Edge/Fog Computing (7 papers), Domain Adaptation and Few-Shot Learning (7 papers) and Advanced Neural Network Applications (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (927 citations), Artificial Intelligence (1.3k citations) and Automotive Engineering (423 citations). Bo Tang has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Haibo He, Haibo He, Steven Kay, Long Chen, Xuemin Hu, Qing Yang, Tao Wei, Zhen Chen, Gerald Hefferman and Ravi Sandhu. Their work appears in journals such as SHILAP Revista de lepidopterología, Chemistry of Materials and Proceedings of the IEEE.
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.