Hao Bian
Impact in
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- Image Enhancement Techniques
- Advanced Image Processing Techniques
- Advanced Vision and Imaging
- Image and Signal Denoising Methods
- Video Surveillance and Tracking Methods
- Media Technology top 5%
- Advanced Image Fusion Techniques
Papers in
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- Digital Imaging for Blood Diseases 2
- Image Enhancement Techniques 2
- Generative Adversarial Networks and Image Synthesis 1
- Video Surveillance and Tracking Methods 1
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- AI in cancer detection 5
- Co-authors
- Haoqian Wang (3 shared papers)Yuanhao Cai (2 shared papers)Radu Timofte (1 shared paper)Jing Lin (1 shared paper)Yulun Zhang (1 shared paper)Yongbing Zhang (6 shared papers)Zhuchen Shao (3 shared papers)Shijie Hao (1 shared paper)
- Journals
- Pattern Recognition Letters (1 paper)IEEE Transactions on Circuits and Systems for Video Technology (1 paper)IEEE Journal of Biomedical and Health Informatics (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
In The Last Decade
Hao Bian
6 papers receiving 337 citations
Hao Bian's Hit Papers
Peers
Comparison fields: 5 of 43
- Computer Vision and Pattern Recognition 291
- Media Technology 114
- Acoustics and Ultrasonics 8
- Instrumentation 20
- Aerospace Engineering 34
Countries citing papers authored by Hao Bian
This map shows the geographic impact of Hao Bian'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 Hao Bian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao Bian more than expected).
Fields of papers citing papers by Hao Bian
This network shows the impact of papers produced by Hao Bian. 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 Hao Bian. The network helps show where Hao Bian may publish in the future.
Co-authors
The 15 scholars most cited alongside Hao Bian, 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 | Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement Hit paper breakdown → | 2023 | 281 |
| 2 | 2020 | 22 | |
| 3 | 2023 | 16 | |
| 4 | 2023 | 13 | |
| 5 | 2023 | 11 | |
| 6 | 2022 | 1 | |
| 7 | 2024 | 0 | |
| 8 | 2023 | 0 |
About Hao Bian
Hao Bian is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Oncology and Radiation, having authored 8 papers that have together received 344 indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Digital Imaging for Blood Diseases (2 papers), Image Enhancement Techniques (2 papers), Colorectal Cancer Screening and Detection (2 papers), Generative Adversarial Networks and Image Synthesis (1 paper), Video Surveillance and Tracking Methods (1 paper) and Cancer-related molecular mechanisms research (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (291 citations), Media Technology (114 citations), Acoustics and Ultrasonics (8 citations), Instrumentation (20 citations) and Aerospace Engineering (34 citations). Hao Bian has collaborated with scholars based in China and Germany. Frequent co-authors include Haoqian Wang, Yuanhao Cai, Radu Timofte, Jing Lin, Yulun Zhang, Yongbing Zhang, Zhuchen Shao, Shijie Hao, Guojun Liu and Shaohui Liu. Their work appears in journals such as Pattern Recognition Letters, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Journal of Biomedical and Health Informatics and Proceedings of the AAAI Conference on Artificial Intelligence.
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.