Qiangchang Wang
- Computer Vision and Pattern Recognition top 5%
- Experimental and Cognitive Psychology top 5%
- Artificial Intelligence
- Signal Processing
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Guodong GuoFanglei XueZichang TanYilong YinYuanjie ZhengGongping YangWeidong JinXinjian Chen
- Topics
- Face and Expression Recognition (4 papers)Face recognition and analysis (4 papers)COVID-19 diagnosis using AI (3 papers)
- Cited by
- Experimental and Cognitive PsychologyComputer Vision and Pattern RecognitionHuman-Computer Interaction
- Journals
- NeurocomputingIEEE Transactions on Information Forensics and SecurityIEEE Signal Processing Letters
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Qiangchang Wang
8 papers receiving 378 citations
Hit Papers
Peers
Comparison fields: 5 of 58
- Computer Vision and Pattern Recognition 273
- Experimental and Cognitive Psychology 192
- Artificial Intelligence 49
- Signal Processing 32
- Radiology, Nuclear Medicine and Imaging 32
Countries citing papers authored by Qiangchang Wang
This map shows the geographic impact of Qiangchang Wang'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 Qiangchang Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qiangchang Wang more than expected).
Fields of papers citing papers by Qiangchang Wang
This network shows the impact of papers produced by Qiangchang Wang. 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 Qiangchang Wang. The network helps show where Qiangchang Wang may publish in the future.
Co-authorship network of co-authors of Qiangchang Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Qiangchang Wang. A scholar is included among the top collaborators of Qiangchang Wang 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 Qiangchang Wang. Qiangchang Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 3 | |
| 8 | 75 | |
| 9 | TransFER: Learning Relation-aware Facial Expression Representations with Transformersbreakdown → | 186 |
| 10 | 4 | |
| 11 | 35 | |
| 12 | 73 |
About Qiangchang Wang
Qiangchang Wang is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Radiology, Nuclear Medicine and Imaging, having authored 12 papers that have together received 382 indexed citations. Recurring topics across this work include Face and Expression Recognition (4 papers), Face recognition and analysis (4 papers) and COVID-19 diagnosis using AI (3 papers). The work is most often cited by research in Experimental and Cognitive Psychology (192 citations), Computer Vision and Pattern Recognition (273 citations) and Human-Computer Interaction (25 citations). Qiangchang Wang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Guodong Guo, Fanglei Xue, Zichang Tan, Yilong Yin, Yuanjie Zheng, Gongping Yang, Weidong Jin, Xinjian Chen, Brad R. Humphreys and Min Jiang. Their work appears in journals such as Neurocomputing, IEEE Transactions on Information Forensics and Security and IEEE Signal Processing Letters.
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.