Helong Zhou
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Signal Processing
- Automotive Engineering
- Media Technology
- Topics
- Advanced Neural Network Applications (5 papers)Domain Adaptation and Few-Shot Learning (4 papers)Advanced Image and Video Retrieval Techniques (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Partner nations
- ChinaTaiwanUnited States
In The Last Decade
Helong Zhou
6 papers receiving 292 citations
Hit Papers
Peers
Comparison fields: 5 of 59
- Computer Vision and Pattern Recognition 152
- Artificial Intelligence 127
- Signal Processing 41
- Automotive Engineering 37
- Media Technology 21
Countries citing papers authored by Helong Zhou
This map shows the geographic impact of Helong Zhou'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 Helong Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Helong Zhou more than expected).
Fields of papers citing papers by Helong Zhou
This network shows the impact of papers produced by Helong Zhou. 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 Helong Zhou. The network helps show where Helong Zhou may publish in the future.
Co-authorship network of co-authors of Helong Zhou
This figure shows the co-authorship network connecting the top 25 collaborators of Helong Zhou. A scholar is included among the top collaborators of Helong Zhou based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Helong Zhou. Helong Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 48 | |
| 2 | 2 | |
| 3 | 77 | |
| 4 | 29 | |
| 5 | Cross-Image Relational Knowledge Distillation for Semantic Segmentationbreakdown → | 141 |
| 6 | 1 |
About Helong Zhou
Helong Zhou is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 6 papers that have together received 298 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Advanced Image and Video Retrieval Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (152 citations), Artificial Intelligence (127 citations) and Signal Processing (41 citations). Helong Zhou has collaborated with scholars based in China, Taiwan and United States. Frequent co-authors include Zhulin An, Chuanguang Yang, Yongjun Xu, Xue Jiang, Qian Zhang, Qian Zhang, Shaoyu Chen, Qian Zhang, Bo Jiang and Chang Huang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
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.