Jianbing Shen
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Biomedical Engineering
- Computational Mechanics
- Control and Systems Engineering
- Topics
- Multimodal Machine Learning Applications (3 papers)Domain Adaptation and Few-Shot Learning (2 papers)Advanced Image and Video Retrieval Techniques (1 paper)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputer Graphics and Computer-Aided Design
- Journals
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Proceedings of the AAAI Conference on Artificial IntelligenceJisuanji gongcheng yu sheji
- Partner nations
- ChinaMacaoSwitzerland
In The Last Decade
Jianbing Shen
6 papers receiving 126 citations
Peers
Comparison fields: 5 of 34
- Computer Vision and Pattern Recognition 108
- Artificial Intelligence 52
- Biomedical Engineering 7
- Computational Mechanics 6
- Control and Systems Engineering 6
Countries citing papers authored by Jianbing Shen
This map shows the geographic impact of Jianbing Shen'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 Jianbing Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianbing Shen more than expected).
Fields of papers citing papers by Jianbing Shen
This network shows the impact of papers produced by Jianbing Shen. 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 Jianbing Shen. The network helps show where Jianbing Shen may publish in the future.
Co-authorship network of co-authors of Jianbing Shen
This figure shows the co-authorship network connecting the top 25 collaborators of Jianbing Shen. A scholar is included among the top collaborators of Jianbing Shen 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 Jianbing Shen. Jianbing Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 10 | |
| 3 | 31 | |
| 4 | 82 | |
| 5 | 2 | |
| 6 | Method of texture segmentation based on wavelet-transform and GMRF | 1 |
About Jianbing Shen
Jianbing Shen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering, having authored 6 papers that have together received 127 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (3 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Advanced Image and Video Retrieval Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (108 citations), Artificial Intelligence (52 citations) and Computer Graphics and Computer-Aided Design (5 citations). Jianbing Shen has collaborated with scholars based in China, Macao and Switzerland. Frequent co-authors include Wenguan Wang, Yanwei Pang, Ling Shao, Jifeng Dai, Wei Liang, Hanqing Wang, Luc Van Gool, Yilong Yin, Xiushan Nie and Xiankai Lu. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Proceedings of the AAAI Conference on Artificial Intelligence and Jisuanji gongcheng yu sheji.
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.