Haoze Wu
Impact in
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- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
Papers in
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- Human Pose and Action Recognition 4
- Advanced Neural Network Applications 3
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- Adversarial Robustness in Machine Learning 4
- Co-authors
- Zheng-Jun Zha (4 shared papers)Clark Barrett (6 shared papers)Zhenzhong Chen (2 shared papers)Jiawei Liu (2 shared papers)Meng Wang (2 shared papers)Xin Wen (1 shared paper)Dong Liu (1 shared paper)Xuejin Chen (1 shared paper)
- Journals
- Proceedings of the ACM on Programming Languages (1 paper)Advanced Engineering Informatics (1 paper)Cities (1 paper)Sensors (1 paper)Scientific Reports (1 paper)
- Partner nations
- ChinaUnited StatesIsrael
In The Last Decade
Haoze Wu
15 papers receiving 65 citations
Peers
Comparison fields: 5 of 34
- Computer Vision and Pattern Recognition 32
- Software 4
- Artificial Intelligence 28
- Computer Science Applications 4
- Signal Processing 6
Countries citing papers authored by Haoze Wu
This map shows the geographic impact of Haoze Wu'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 Haoze Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haoze Wu more than expected).
Fields of papers citing papers by Haoze Wu
This network shows the impact of papers produced by Haoze Wu. 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 Haoze Wu. The network helps show where Haoze Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Haoze Wu, 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 | 2020 | 10 | |
| 2 | 2019 | 10 | |
| 3 | 2024 | 8 | |
| 4 | 2019 | 6 | |
| 5 | 2023 | 5 | |
| 6 | 2020 | 5 | |
| 7 | 2020 | 5 | |
| 8 | 2022 | 4 | |
| 9 | 2021 | 3 | |
| 10 | 2025 | 3 | |
| 11 | 2020 | 2 | |
| 12 | 2024 | 1 | |
| 13 | 2024 | 1 | |
| 14 | 2023 | 1 | |
| 15 | 2023 | 1 | |
| 16 | 2024 | 0 | |
| 17 | 2025 | 0 | |
| 18 | 2023 | 0 | |
| 19 | 2022 | 0 |
About Haoze Wu
Haoze Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, Control and Systems Engineering and Electrical and Electronic Engineering, having authored 19 papers that have together received 65 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (4 papers), Human Pose and Action Recognition (4 papers), Gait Recognition and Analysis (4 papers), Advanced Neural Network Applications (3 papers), Fault Detection and Control Systems (3 papers), Autonomous Vehicle Technology and Safety (2 papers), Advanced Fiber Optic Sensors (2 papers) and Photonic and Optical Devices (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (32 citations), Software (4 citations), Artificial Intelligence (28 citations), Computer Science Applications (4 citations) and Signal Processing (6 citations). Haoze Wu has collaborated with scholars based in China, United States and Israel. Frequent co-authors include Zheng-Jun Zha, Clark Barrett, Zhenzhong Chen, Jiawei Liu, Meng Wang, Xin Wen, Dong Liu, Xuejin Chen, Mykel J. Kochenderfer and Xuyun Fu. Their work appears in journals such as Proceedings of the ACM on Programming Languages, Advanced Engineering Informatics, Cities, Sensors and Scientific Reports.
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.