Yatong Zhou
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 10%
- Automotive Engineering top 10%
- Co-authors
- Chaojun ShiGuizhong LiuLingling LiEnqing DongJingfei HeKuo-Ping LinJiancheng SunXiaodi Zhang
- Topics
- Neural Networks and Applications (12 papers)Sparse and Compressive Sensing Techniques (11 papers)Blind Source Separation Techniques (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEExpert Systems with Applications
- Partner nations
- ChinaTaiwanUnited States
In The Last Decade
Yatong Zhou
64 papers receiving 557 citations
Peers
Comparison fields: 5 of 85
- Artificial Intelligence 214
- Electrical and Electronic Engineering 158
- Computer Vision and Pattern Recognition 145
- Signal Processing 98
- Automotive Engineering 74
Countries citing papers authored by Yatong Zhou
This map shows the geographic impact of Yatong 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 Yatong Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yatong Zhou more than expected).
Fields of papers citing papers by Yatong Zhou
This network shows the impact of papers produced by Yatong 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 Yatong Zhou. The network helps show where Yatong Zhou may publish in the future.
Co-authorship network of co-authors of Yatong Zhou
This figure shows the co-authorship network connecting the top 25 collaborators of Yatong Zhou. A scholar is included among the top collaborators of Yatong 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 Yatong Zhou. Yatong 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 | 1 | |
| 2 | 8 | |
| 3 | 1 | |
| 4 | 14 | |
| 5 | 14 | |
| 6 | 3 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 7 | |
| 10 | 7 | |
| 11 | 1 | |
| 12 | 20 | |
| 13 | 18 | |
| 14 | From Gaussian Processes to the Mixture of Gaussian Processes:A Survey | 2 |
| 15 | The Method of Attribute Weight Distribution in multi-attribute system | 1 |
| 16 | A Comparison of the Dehydration Processes of Al-, Fe2+, and Mg-Sulfates Under Mars Relevant Pressures and Three Temperatures | 1 |
| 17 | 40 | |
| 18 | Application of a Scaling Kernel in Signal Approximation of Least Squares Support Vector Machines | 3 |
| 19 | 1 | |
| 20 | 2 |
About Yatong Zhou
Yatong Zhou is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Signal Processing, having authored 71 papers that have together received 590 indexed citations. Recurring topics across this work include Neural Networks and Applications (12 papers), Sparse and Compressive Sensing Techniques (11 papers) and Blind Source Separation Techniques (8 papers). The work is most often cited by research in Computational Mathematics (10 citations), Signal Processing (98 citations) and Computer Vision and Pattern Recognition (145 citations). Yatong Zhou has collaborated with scholars based in China, Taiwan and United States. Frequent co-authors include Chaojun Shi, Guizhong Liu, Lingling Li, Enqing Dong, Jingfei He, Kuo-Ping Lin, Jiancheng Sun, Xiaodi Zhang, Ching-Hsin Wang and Kuei‐Hsiang Chao. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Expert Systems with Applications.
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.