Fang Jiang
- Cognitive Neuroscience top 1%
- Computer Vision and Pattern Recognition top 2%
- Experimental and Cognitive Psychology top 2%
- Social Psychology top 10%
- Signal Processing top 5%
- Co-authors
- Alice J. O’TooleHervé AbdiVolker BlanzJames V. HaxbyBruno RossionP. Jonathon PhillipsIone FineOsman B. Kavcar
- Topics
- Visual perception and processing mechanisms (33 papers)Multisensory perception and integration (23 papers)Face Recognition and Perception (23 papers)
- Cited by
- Cognitive NeuroscienceExperimental and Cognitive PsychologyComputer Vision and Pattern Recognition
- Journals
- Proceedings of the National Academy of SciencesIEEE Transactions on Pattern Analysis and Machine IntelligenceNeuroImage
- Partner nations
- United StatesChinaBelgium
In The Last Decade
Fang Jiang
83 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 131
- Cognitive Neuroscience 1.3k
- Computer Vision and Pattern Recognition 502
- Experimental and Cognitive Psychology 467
- Social Psychology 135
- Signal Processing 130
Countries citing papers authored by Fang Jiang
This map shows the geographic impact of Fang 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 Fang Jiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fang Jiang more than expected).
Fields of papers citing papers by Fang Jiang
This network shows the impact of papers produced by Fang 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 Fang Jiang. The network helps show where Fang Jiang may publish in the future.
Co-authorship network of co-authors of Fang Jiang
This figure shows the co-authorship network connecting the top 25 collaborators of Fang Jiang. A scholar is included among the top collaborators of Fang 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 Fang Jiang. Fang 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 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 7 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 12 | |
| 10 | 36 | |
| 11 | 11 | |
| 12 | 17 | |
| 13 | 29 | |
| 14 | 4 | |
| 15 | 45 | |
| 16 | 25 | |
| 17 | 11 | |
| 18 | 75 | |
| 19 | 184 | |
| 20 | Several notable issues on visual interpretation of remote sensing image | 1 |
About Fang Jiang
Fang Jiang is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Computer Vision and Pattern Recognition, having authored 89 papers that have together received 1.8k indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (33 papers), Multisensory perception and integration (23 papers) and Face Recognition and Perception (23 papers). The work is most often cited by research in Cognitive Neuroscience (1.3k citations), Experimental and Cognitive Psychology (467 citations) and Computer Vision and Pattern Recognition (502 citations). Fang Jiang has collaborated with scholars based in United States, China and Belgium. Frequent co-authors include Alice J. O’Toole, Hervé Abdi, Volker Blanz, James V. Haxby, Bruno Rossion, P. Jonathon Phillips, Ione Fine, Osman B. Kavcar, Joseph Dunlop and Marc Parent. Their work appears in journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Pattern Analysis and Machine Intelligence and NeuroImage.
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.