Jie Yang
- Computer Vision and Pattern Recognition top 0.05%
- Video Surveillance and Tracking Methods 101
- Advanced Image and Video Retrieval Techniques 98
- Advanced Vision and Imaging 72
- Image Retrieval and Classification Techniques 64
- Image Enhancement Techniques 62
- Advanced Image Processing Techniques 56
- Image and Signal Denoising Methods 52
- Media Technology top 0.1%
- Advanced Image Fusion Techniques 54
- Artificial Intelligence top 0.2%
- Oral Surgery top 1%
- Human-Computer Interaction top 1%
- Co-authors
- Masoumeh ZareapoorNikola KasabovPourya ShamsolmoaliKeren FuDacheng TaoChen GongKuo‐Chen ChouHong‐Bin Shen
- Journals
- Neurocomputing (21 papers)IEEE Access (17 papers)IEEE Transactions on Circuits and Systems for Video Technology (14 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Jie Yang
801 papers receiving 13.5k citations
Peers
Comparison fields: 5 of 208
- Computer Vision and Pattern Recognition 6.5k
- Media Technology 2.0k
- Artificial Intelligence 2.8k
- Oral Surgery 571
- Human-Computer Interaction 334
Countries citing papers authored by Jie Yang
This map shows the geographic impact of Jie Yang'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 Jie Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jie Yang more than expected).
Fields of papers citing papers by Jie Yang
This network shows the impact of papers produced by Jie Yang. 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 Jie Yang. The network helps show where Jie Yang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jie Yang, 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 | 2026 | 0 | |
| 2 | 2026 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 3 | |
| 5 | 2024 | 11 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 6 | |
| 9 | 2024 | 4 | |
| 10 | 2024 | 7 | |
| 11 | 2024 | 4 | |
| 12 | 2023 | 4 | |
| 13 | 2023 | 12 | |
| 14 | 2023 | 9 | |
| 15 | 2023 | 4 | |
| 16 | 2023 | 0 | |
| 17 | 2022 | 0 | |
| 18 | 2021 | 4 | |
| 19 | 2021 | 0 | |
| 20 | 2018 | 51 |
About Jie Yang
Jie Yang is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Artificial Intelligence, Signal Processing and Aerospace Engineering, having authored 896 papers that have together received 14.1k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (101 papers), Advanced Image and Video Retrieval Techniques (98 papers), Advanced Vision and Imaging (72 papers), Image Retrieval and Classification Techniques (64 papers), Image Enhancement Techniques (62 papers), Advanced Image Processing Techniques (56 papers), Advanced Image Fusion Techniques (54 papers) and Image and Signal Denoising Methods (52 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (6.5k citations), Media Technology (2.0k citations), Artificial Intelligence (2.8k citations), Oral Surgery (571 citations) and Human-Computer Interaction (334 citations). Jie Yang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Masoumeh Zareapoor, Nikola Kasabov, Pourya Shamsolmoali, Keren Fu, Dacheng Tao, Chen Gong, Kuo‐Chen Chou, Hong‐Bin Shen, Irene Yu‐Hua Gu and Xiangjian He. Their work appears in journals such as Neurocomputing, IEEE Access, IEEE Transactions on Circuits and Systems for Video Technology, Pattern Recognition Letters and Pattern Recognition.
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.