Mingyue Niu
- Experimental and Cognitive Psychology top 2%
- Artificial Intelligence top 5%
- Social Psychology top 5%
- Cognitive Neuroscience top 10%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Jianhua TaoZheng LianBin LiuYa LiJian HuangZiping ZhaoLang HeWei Dang
- Topics
- Emotion and Mood Recognition (28 papers)Mental Health via Writing (9 papers)Music and Audio Processing (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsFrontiers in Plant Science
- Partner nations
- ChinaUnited KingdomGermany
In The Last Decade
Mingyue Niu
40 papers receiving 947 citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Experimental and Cognitive Psychology 605
- Artificial Intelligence 291
- Social Psychology 239
- Cognitive Neuroscience 166
- Computer Vision and Pattern Recognition 161
Countries citing papers authored by Mingyue Niu
This map shows the geographic impact of Mingyue Niu'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 Mingyue Niu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingyue Niu more than expected).
Fields of papers citing papers by Mingyue Niu
This network shows the impact of papers produced by Mingyue Niu. 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 Mingyue Niu. The network helps show where Mingyue Niu may publish in the future.
Co-authorship network of co-authors of Mingyue Niu
This figure shows the co-authorship network connecting the top 25 collaborators of Mingyue Niu. A scholar is included among the top collaborators of Mingyue Niu 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 Mingyue Niu. Mingyue Niu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 11 | |
| 3 | 5 | |
| 4 | 12 | |
| 5 | 10 | |
| 6 | 2 | |
| 7 | 6 | |
| 8 | 24 | |
| 9 | Deep learning for depression recognition with audiovisual cues: A reviewbreakdown → | 145 |
| 10 | 101 | |
| 11 | Micro-Expression Recognition Based on Multiple Aggregation Networks | 3 |
| 12 | 104 | |
| 13 | 9 | |
| 14 | 28 | |
| 15 | 25 | |
| 16 | 8 | |
| 17 | 3 | |
| 18 | 40 | |
| 19 | 12 | |
| 20 | 4 |
About Mingyue Niu
Mingyue Niu is a scholar working on Experimental and Cognitive Psychology, Signal Processing and Computer Vision and Pattern Recognition, having authored 40 papers that have together received 972 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (28 papers), Mental Health via Writing (9 papers) and Music and Audio Processing (6 papers). The work is most often cited by research in Experimental and Cognitive Psychology (605 citations), Applied Psychology (82 citations) and Signal Processing (150 citations). Mingyue Niu has collaborated with scholars based in China, United Kingdom and Germany. Frequent co-authors include Jianhua Tao, Zheng Lian, Bin Liu, Ya Li, Jian Huang, Jian Huang, Ziping Zhao, Lang He, Wei Dang and Chenguang Guo. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Frontiers in Plant Science.
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.