Jianfeng Feng
- Cognitive Neuroscience top 0.2%
- Neural dynamics and brain function 155
- Functional Brain Connectivity Studies 97
- Statistical and Nonlinear Physics top 0.5%
- stochastic dynamics and bifurcation 56
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- Advanced Neuroimaging Techniques and Applications 38
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- Neural Networks and Applications 39
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- Neuroscience and Neural Engineering 23
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- Nonlinear Dynamics and Pattern Formation 23
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- Advanced Memory and Neural Computing 22
- Co-authors
- Edmund T. RollsChu‐Chung HuangWei ChengChing‐Po LinYanwei FuLi ZhangMarc JoliotXiatian Zhu
- Cited by
- Cognitive NeuroscienceComputer Vision and Pattern RecognitionExperimental and Cognitive Psychology
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Jianfeng Feng
343 papers receiving 12.7k citations
Hit Papers
Peers
Comparison fields: 5 of 205
- Cognitive Neuroscience 6.1k
- Computer Vision and Pattern Recognition 2.6k
- Experimental and Cognitive Psychology 1.2k
- Statistical and Nonlinear Physics 984
- Radiology, Nuclear Medicine and Imaging 1.7k
Countries citing papers authored by Jianfeng Feng
This map shows the geographic impact of Jianfeng Feng'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 Jianfeng Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianfeng Feng more than expected).
Fields of papers citing papers by Jianfeng Feng
This network shows the impact of papers produced by Jianfeng Feng. 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 Jianfeng Feng. The network helps show where Jianfeng Feng may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jianfeng Feng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 10 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 25 | |
| 8 | 2023 | 8 | |
| 9 | 2023 | 7 | |
| 10 | 2022 | 10 | |
| 11 | 2022 | 11 | |
| 12 | 2022 | 10 | |
| 13 | 2022 | 19 | |
| 14 | Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformersbreakdown → | 2021 | 2386 |
| 15 | 2021 | 5 | |
| 16 | 2020 | 37 | |
| 17 | 2020 | 5 | |
| 18 | 2018 | 52 | |
| 19 | 2008 | 117 | |
| 20 | 2008 | 56 |
About Jianfeng Feng
Jianfeng Feng is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics and Cellular and Molecular Neuroscience, having authored 358 papers that have together received 13.0k indexed citations. Recurring topics across this work include Neural dynamics and brain function (155 papers), Functional Brain Connectivity Studies (97 papers), stochastic dynamics and bifurcation (56 papers), Neural Networks and Applications (39 papers), Advanced Neuroimaging Techniques and Applications (38 papers), Neuroscience and Neural Engineering (23 papers), Nonlinear Dynamics and Pattern Formation (23 papers) and Advanced Memory and Neural Computing (22 papers). The work is most often cited by research in Cognitive Neuroscience (6.1k citations), Computer Vision and Pattern Recognition (2.6k citations) and Experimental and Cognitive Psychology (1.2k citations). Jianfeng Feng has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Edmund T. Rolls, Chu‐Chung Huang, Wei Cheng, Ching‐Po Lin, Yanwei Fu, Li Zhang, Marc Joliot, Xiatian Zhu, Jiachen Lu and Tao Xiang. Their work appears in journals such as Physical Review Letters, Journal of Neuroscience and PLoS ONE.
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.