Feiping Nie
Impact in
- Computer Vision and Pattern Recognition top 0.01%
- Face and Expression Recognition
- Advanced Image and Video Retrieval Techniques
- Image Retrieval and Classification Techniques
- Video Surveillance and Tracking Methods
- Computational Mathematics top 0.1%
Papers in
-
- Face and Expression Recognition 506
- Advanced Image and Video Retrieval Techniques 122
- Image Retrieval and Classification Techniques 100
- Urban Studies 112
- Advanced Computing and Algorithms 112
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (89 papers)IEEE Transactions on Knowledge and Data Engineering (68 papers)Neurocomputing (58 papers)Pattern Recognition (48 papers)IEEE Transactions on Image Processing (39 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Feiping Nie
743 papers receiving 32.6k citations
Hit Papers
Peers
Comparison fields: 5 of 194
- Computer Vision and Pattern Recognition 23.5k
- Computational Mathematics 608
- Media Technology 6.1k
- Urban Studies 3.1k
- Artificial Intelligence 16.1k
Countries citing papers authored by Feiping Nie
This map shows the geographic impact of Feiping Nie'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 Feiping Nie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feiping Nie more than expected).
Fields of papers citing papers by Feiping Nie
This network shows the impact of papers produced by Feiping Nie. 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 Feiping Nie. The network helps show where Feiping Nie may publish in the future.
Co-authors
The 25 scholars most cited alongside Feiping Nie, 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 | 2025 | 2 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 6 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 2 | |
| 9 | 2024 | 18 | |
| 10 | 2024 | 2 | |
| 11 | 2023 | 5 | |
| 12 | 2023 | 20 | |
| 13 | 2023 | 10 | |
| 14 | 2023 | 5 | |
| 15 | 2023 | 35 | |
| 16 | 2023 | 8 | |
| 17 | 2023 | 4 | |
| 18 | 2023 | 1 | |
| 19 | 2023 | 5 | |
| 20 | 2023 | 7 |
About Feiping Nie
Feiping Nie is a scholar working on Computer Vision and Pattern Recognition, Urban Studies, Media Technology, Artificial Intelligence and Computational Mathematics, having authored 807 papers that have together received 33.1k indexed citations. Recurring topics across this work include Face and Expression Recognition (506 papers), Advanced Clustering Algorithms Research (180 papers), Remote-Sensing Image Classification (156 papers), Advanced Image and Video Retrieval Techniques (122 papers), Sparse and Compressive Sensing Techniques (112 papers), Advanced Computing and Algorithms (112 papers), Image Retrieval and Classification Techniques (100 papers) and Text and Document Classification Technologies (89 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (23.5k citations), Computational Mathematics (608 citations), Media Technology (6.1k citations), Urban Studies (3.1k citations) and Artificial Intelligence (16.1k citations). Feiping Nie has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Heng Huang, Xuelong Li, Xuelong Li, Rong Wang, Yi Yang, Changshui Zhang, Chris Ding, Xiao Cai, Shiming Xiang and Xiaoqian Wang. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering, Neurocomputing, Pattern Recognition and IEEE Transactions on Image Processing.
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.