Degang Yang
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Artificial Intelligence top 10%
- Statistical and Nonlinear Physics top 5%
- Computational Theory and Mathematics top 10%
- Co-authors
- Yong WangKwok‐Wo WongXiaofeng LiaoJie ZhouHuaqian YangTingting SongYingze SongTao Xiang
- Topics
- Neural Networks Stability and Synchronization (17 papers)Nonlinear Dynamics and Pattern Formation (10 papers)Advanced Neural Network Applications (9 papers)
In The Last Decade
Degang Yang
55 papers receiving 482 citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Computer Vision and Pattern Recognition 211
- Computer Networks and Communications 140
- Artificial Intelligence 128
- Statistical and Nonlinear Physics 96
- Computational Theory and Mathematics 39
Countries citing papers authored by Degang Yang
This map shows the geographic impact of Degang 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 Degang Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Degang Yang more than expected).
Fields of papers citing papers by Degang Yang
This network shows the impact of papers produced by Degang 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 Degang Yang. The network helps show where Degang Yang may publish in the future.
Co-authorship network of co-authors of Degang Yang
This figure shows the co-authorship network connecting the top 25 collaborators of Degang Yang. A scholar is included among the top collaborators of Degang 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 Degang Yang. Degang 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 | 10 | |
| 2 | 6 | |
| 3 | 14 | |
| 4 | 13 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 24 | |
| 11 | 1 | |
| 12 | 5 | |
| 13 | 9 | |
| 14 | 18 | |
| 15 | 3 | |
| 16 | 0 | |
| 17 | 3 | |
| 18 | 8 | |
| 19 | 10 | |
| 20 | A Research into Application of Data Mining Technology in Intrusion Detection | 2 |
About Degang Yang
Degang Yang is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 59 papers that have together received 515 indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (17 papers), Nonlinear Dynamics and Pattern Formation (10 papers) and Advanced Neural Network Applications (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (211 citations), Statistical and Nonlinear Physics (96 citations) and Computer Networks and Communications (140 citations). Degang Yang has collaborated with scholars based in China, Hong Kong and Qatar. Frequent co-authors include Yong Wang, Kwok‐Wo Wong, Xiaofeng Liao, Jie Zhou, Huaqian Yang, Xiaofeng Liao, Tingting Song, Yingze Song, Tao Xiang and Wanli Zhang. Their work appears in journals such as Expert Systems with Applications, Analytica Chimica Acta and Physics Letters A.
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.