Cong Hu
Impact in
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- Face and Expression Recognition
- Robotic Path Planning Algorithms
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Face recognition and analysis
Papers in
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- Face and Expression Recognition 13
- Advanced Image and Video Retrieval Techniques 7
- Face recognition and analysis 6
- Generative Adversarial Networks and Image Synthesis 5
- Robotic Path Planning Algorithms 5
- Image Retrieval and Classification Techniques 4
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- Adversarial Robustness in Machine Learning 7
- Domain Adaptation and Few-Shot Learning 4
- Co-authors
- Xiao‐Jun Wu (21 shared papers)Josef Kittler (5 shared papers)Zhenqiu Shu (7 shared papers)Quanjun Yin (5 shared papers)Yue Hu (5 shared papers)Rui Wang (3 shared papers)Zhenhua Feng (3 shared papers)Honghui Fan (2 shared papers)
- Journals
- Neural Processing Letters (3 papers)Applied Soft Computing (2 papers)Forests (2 papers)IEEE Access (2 papers)IEEE Transactions on Information Forensics and Security (2 papers)
- Partner nations
- ChinaUnited KingdomAustralia
In The Last Decade
Cong Hu
59 papers receiving 444 citations
Peers
Comparison fields: 5 of 95
- Computer Vision and Pattern Recognition 211
- Computational Mathematics 4
- Artificial Intelligence 155
- Signal Processing 38
- Media Technology 19
Countries citing papers authored by Cong Hu
This map shows the geographic impact of Cong Hu'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 Cong Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cong Hu more than expected).
Fields of papers citing papers by Cong Hu
This network shows the impact of papers produced by Cong Hu. 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 Cong Hu. The network helps show where Cong Hu may publish in the future.
Co-authors
The 25 scholars most cited alongside Cong Hu, 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 66 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 56 | |
| 2 | 2022 | 52 | |
| 3 | 2017 | 30 | |
| 4 | 2024 | 22 | |
| 5 | 2022 | 19 | |
| 6 | 2018 | 15 | |
| 7 | 2020 | 15 | |
| 8 | 2023 | 15 | |
| 9 | 2020 | 13 | |
| 10 | 2022 | 13 | |
| 11 | 2020 | 13 | |
| 12 | 2019 | 12 | |
| 13 | 2022 | 12 | |
| 14 | 2023 | 11 | |
| 15 | 2024 | 11 | |
| 16 | 2018 | 11 | |
| 17 | 2023 | 10 | |
| 18 | 2024 | 9 | |
| 19 | 2024 | 8 | |
| 20 | 2019 | 7 |
About Cong Hu
Cong Hu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Signal Processing and Urban Studies, having authored 66 papers that have together received 447 indexed citations. Recurring topics across this work include Face and Expression Recognition (13 papers), Adversarial Robustness in Machine Learning (7 papers), Advanced Image and Video Retrieval Techniques (7 papers), Face recognition and analysis (6 papers), Generative Adversarial Networks and Image Synthesis (5 papers), Robotic Path Planning Algorithms (5 papers), Image Retrieval and Classification Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (211 citations), Computational Mathematics (4 citations), Artificial Intelligence (155 citations), Signal Processing (38 citations) and Media Technology (19 citations). Cong Hu has collaborated with scholars based in China, United Kingdom and Australia. Frequent co-authors include Xiao‐Jun Wu, Josef Kittler, Zhenqiu Shu, Quanjun Yin, Yue Hu, Rui Wang, Zhenhua Feng, Honghui Fan, Tianyang Xu and Pu Huang. Their work appears in journals such as Neural Processing Letters, Applied Soft Computing, Forests, IEEE Access and IEEE Transactions on Information Forensics and Security.
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.