Jin Li
Impact in
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- Multimodal Machine Learning Applications
- Advanced Data Compression Techniques
- Artificial Intelligence top 2%
- Domain Adaptation and Few-Shot Learning
- Wireless Signal Modulation Classification
- Neural Networks and Reservoir Computing
Papers in
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- Advanced Neural Network Applications 7
- Advanced Data Compression Techniques 7
- Advanced Image and Video Retrieval Techniques 7
- Image and Signal Denoising Methods 6
Jin Li
112 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 132
- Computer Vision and Pattern Recognition 343
- Artificial Intelligence 528
- Signal Processing 141
- Electrical and Electronic Engineering 477
- Computer Networks and Communications 160
Countries citing papers authored by Jin Li
This map shows the geographic impact of Jin Li'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 Jin Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Li more than expected).
Fields of papers citing papers by Jin Li
This network shows the impact of papers produced by Jin Li. 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 Jin Li. The network helps show where Jin Li may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jin Li, 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 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 0 | |
| 10 | 2024 | 2 | |
| 11 | 2024 | 0 | |
| 12 | 2021 | 15 | |
| 13 | 2020 | 9 | |
| 14 | 2020 | 23 | |
| 15 | 2020 | 15 | |
| 16 | Dynamic Prediction of Origin-Destination Flows Using Fusion Line Graph Convolutional Networks. | 2019 | 3 |
| 17 | 2017 | 141 | |
| 18 | 2017 | 190 | |
| 19 | A Strong Tracking Unscented Kalman Filter and its Application in Passive Target Tracking | 2005 | 1 |
| 20 | Fast Training Algorithm of BP Wavelet Neural Network | 2001 | 6 |
About Jin Li
Jin Li is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Control and Systems Engineering and Computer Science Applications, having authored 130 papers that have together received 1.6k indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (8 papers), Domain Adaptation and Few-Shot Learning (7 papers), Heart Rate Variability and Autonomic Control (7 papers), Advanced Neural Network Applications (7 papers), Advanced Data Compression Techniques (7 papers), Advanced Image and Video Retrieval Techniques (7 papers), Topic Modeling (6 papers) and Image and Signal Denoising Methods (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (343 citations), Artificial Intelligence (528 citations), Signal Processing (141 citations), Electrical and Electronic Engineering (477 citations) and Computer Networks and Communications (160 citations). Jin Li has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Danshi Wang, Min Zhang, Chuang Song, Xue Chen, Ze Li, Meixia Fu, Min Zhang, Yue Cui, Jianqiang Li and Ze Li. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Optics Express, Expert Systems with Applications, Knowledge-Based Systems and IEEE Transactions on Multimedia.
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.