Yongxin Yang
- Computer Vision and Pattern Recognition top 2%
- Biomedical Engineering
- Artificial Intelligence
- Aerospace Engineering
- Signal Processing
- Co-authors
- Tao XiangKaiyang ZhouAndrea CavallaroTimothy M. HospedalesZhigang ChuYang YangAleš LeonardisSteven McDonagh
- Topics
- Advanced Neural Network Applications (4 papers)Advanced Image and Video Retrieval Techniques (3 papers)Image and Signal Denoising Methods (2 papers)
- Journals
- Journal of Sound and VibrationNeurocomputingACM Transactions on Architecture and Code Optimization
- Partner nations
- ChinaUnited KingdomSweden
In The Last Decade
Yongxin Yang
9 papers receiving 631 citations
Hit Papers
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 571
- Biomedical Engineering 195
- Artificial Intelligence 83
- Aerospace Engineering 55
- Signal Processing 43
Countries citing papers authored by Yongxin Yang
This map shows the geographic impact of Yongxin Yang'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 Yongxin Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yongxin Yang more than expected).
Fields of papers citing papers by Yongxin Yang
This network shows the impact of papers produced by Yongxin Yang. 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 Yongxin Yang. The network helps show where Yongxin Yang may publish in the future.
Co-authorship network of co-authors of Yongxin Yang
This figure shows the co-authorship network connecting the top 25 collaborators of Yongxin Yang. A scholar is included among the top collaborators of Yongxin Yang 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 Yongxin Yang. Yongxin Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | Omni-Scale Feature Learning for Person Re-Identificationbreakdown → | 581 |
| 8 | 31 | |
| 9 | Deep Neural Networks for Sketch Recognition. | 24 |
| 10 | RESEARCH PROGRESS OF CROSS CORRELATION ALGORITHMS IN PARTICLE IMAGE VELOCIMETRY | 1 |
About Yongxin Yang
Yongxin Yang is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Artificial Intelligence, having authored 10 papers that have together received 654 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Image and Signal Denoising Methods (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (571 citations), Biomedical Engineering (195 citations) and Signal Processing (43 citations). Yongxin Yang has collaborated with scholars based in China, United Kingdom and Sweden. Frequent co-authors include Tao Xiang, Kaiyang Zhou, Andrea Cavallaro, Timothy M. Hospedales, Zhigang Chu, Yang Yang, Aleš Leonardis, Steven McDonagh, Nanqing Dong and Eduardo Pérez-Pellitero. Their work appears in journals such as Journal of Sound and Vibration, Neurocomputing and ACM Transactions on Architecture and Code Optimization.
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.