Bihan Jiang
- Experimental and Cognitive Psychology top 1%
- Computer Vision and Pattern Recognition top 1%
- Cognitive Neuroscience top 10%
- Artificial Intelligence top 5%
- Social Psychology top 5%
- Co-authors
- Maja PantićMichel ValstarMarc MéhuKlaus R. SchererBrais MartínezBjörn W. SchullerFlorian EybenSebastian Schnieder
- Topics
- Emotion and Mood Recognition (9 papers)Face recognition and analysis (7 papers)Face and Expression Recognition (6 papers)
- Cited by
- Experimental and Cognitive PsychologyComputer Vision and Pattern RecognitionHuman-Computer Interaction
- Journals
- IEEE Transactions on CyberneticsIEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)IEEE Transactions on Affective Computing
- Partner nations
- United KingdomNetherlandsSwitzerland
In The Last Decade
Bihan Jiang
9 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 75
- Experimental and Cognitive Psychology 1.1k
- Computer Vision and Pattern Recognition 874
- Cognitive Neuroscience 222
- Artificial Intelligence 218
- Social Psychology 198
Countries citing papers authored by Bihan Jiang
This map shows the geographic impact of Bihan Jiang'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 Bihan Jiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bihan Jiang more than expected).
Fields of papers citing papers by Bihan Jiang
This network shows the impact of papers produced by Bihan Jiang. 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 Bihan Jiang. The network helps show where Bihan Jiang may publish in the future.
Co-authorship network of co-authors of Bihan Jiang
This figure shows the co-authorship network connecting the top 25 collaborators of Bihan Jiang. A scholar is included among the top collaborators of Bihan Jiang 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 Bihan Jiang. Bihan Jiang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 208 | |
| 2 | 32 | |
| 3 | 2 | |
| 4 | 101 | |
| 5 | AVEC 2013breakdown → | 409 |
| 6 | 216 | |
| 7 | 5 | |
| 8 | 277 | |
| 9 | 171 |
About Bihan Jiang
Bihan Jiang is a scholar working on Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition and Human-Computer Interaction, having authored 9 papers that have together received 1.4k indexed citations. Recurring topics across this work include Emotion and Mood Recognition (9 papers), Face recognition and analysis (7 papers) and Face and Expression Recognition (6 papers). The work is most often cited by research in Experimental and Cognitive Psychology (1.1k citations), Computer Vision and Pattern Recognition (874 citations) and Human-Computer Interaction (122 citations). Bihan Jiang has collaborated with scholars based in United Kingdom, Netherlands and Switzerland. Frequent co-authors include Maja Pantić, Michel Valstar, Marc Méhu, Klaus R. Scherer, Brais Martínez, Björn W. Schuller, Florian Eyben, Sebastian Schnieder, Roddy Cowie and Kirsty Smith. Their work appears in journals such as IEEE Transactions on Cybernetics, IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) and IEEE Transactions on Affective Computing.
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.