Hexin Bai
Impact in
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- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
- Visual Attention and Saliency Detection
- Advanced Vision and Imaging
- Image Enhancement Techniques
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- Fire Detection and Safety Systems
Papers in
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- Video Surveillance and Tracking Methods 3
- Advanced Image and Video Retrieval Techniques 1
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- Fire Detection and Safety Systems 2
- Co-authors
- Haibin Ling (6 shared papers)Peng Chu (4 shared papers)Liting Lin (2 shared papers)Heng Fan (2 shared papers)Sijia Yu (2 shared papers)Ge Deng (2 shared papers)Yong Xu (2 shared papers)Fan Yang (2 shared papers)
- Journals
- International Journal of Computer Vision (1 paper)Neural Computing and Applications (1 paper)Digital Discovery (1 paper)PubMed (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Hexin Bai
6 papers receiving 1.1k citations
Hexin Bai's Hit Papers
Peers
Comparison fields: 5 of 62
- Computer Vision and Pattern Recognition 1.1k
- Safety, Risk, Reliability and Quality 246
- Aerospace Engineering 284
- Human-Computer Interaction 42
- Global and Planetary Change 124
Countries citing papers authored by Hexin Bai
This map shows the geographic impact of Hexin Bai'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 Hexin Bai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hexin Bai more than expected).
Fields of papers citing papers by Hexin Bai
This network shows the impact of papers produced by Hexin Bai. 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 Hexin Bai. The network helps show where Hexin Bai may publish in the future.
Co-authors
The 21 scholars most cited alongside Hexin Bai, 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 | LaSOT: A High-Quality Benchmark for Large-Scale Single Object Tracking Hit paper breakdown → | 2019 | 970 |
| 2 | 2020 | 151 | |
| 3 | 2021 | 23 | |
| 4 | 2023 | 7 | |
| 5 | 2023 | 2 | |
| 6 | 2021 | 1 |
About Hexin Bai
Hexin Bai is a scholar working on Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality, Catalysis, Biomedical Engineering and Materials Chemistry, having authored 6 papers that have together received 1.2k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (3 papers), Catalysis and Oxidation Reactions (2 papers), Fire Detection and Safety Systems (2 papers), Machine Learning in Materials Science (2 papers), Advanced Chemical Sensor Technologies (1 paper), Advanced Image and Video Retrieval Techniques (1 paper), Dental Radiography and Imaging (1 paper) and Computational Drug Discovery Methods (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Safety, Risk, Reliability and Quality (246 citations), Aerospace Engineering (284 citations), Human-Computer Interaction (42 citations) and Global and Planetary Change (124 citations). Hexin Bai has collaborated with scholars based in United States and China. Frequent co-authors include Haibin Ling, Peng Chu, Liting Lin, Heng Fan, Sijia Yu, Ge Deng, Yong Xu, Fan Yang, Chunyuan Liao and Harshit. Their work appears in journals such as International Journal of Computer Vision, Neural Computing and Applications, Digital Discovery and PubMed.
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.