Yimu Ji
Impact in
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- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Face recognition and analysis
- Face and Expression Recognition
- Multimodal Machine Learning Applications
- Media Technology top 5%
Papers in
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- Advanced Neural Network Applications 19
- Video Surveillance and Tracking Methods 17
- Advanced Image and Video Retrieval Techniques 8
- Face recognition and analysis 7
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- Anomaly Detection Techniques and Applications 6
Yimu Ji
92 papers receiving 731 citations
Peers
Comparison fields: 5 of 103
- Computer Vision and Pattern Recognition 406
- Media Technology 61
- Artificial Intelligence 218
- Signal Processing 56
- Information Systems 110
Countries citing papers authored by Yimu Ji
This map shows the geographic impact of Yimu Ji'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 Yimu Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yimu Ji more than expected).
Fields of papers citing papers by Yimu Ji
This network shows the impact of papers produced by Yimu Ji. 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 Yimu Ji. The network helps show where Yimu Ji may publish in the future.
Co-authors
The 25 scholars most cited alongside Yimu Ji, 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 | 3 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 2 | |
| 5 | 2025 | 0 | |
| 6 | 2025 | 0 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 6 | |
| 9 | 2024 | 2 | |
| 10 | 2023 | 5 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 1 | |
| 13 | 2022 | 1 | |
| 14 | 2021 | 2 | |
| 15 | 2021 | 2 | |
| 16 | 2020 | 2 | |
| 17 | 2019 | 12 | |
| 18 | 2018 | 28 | |
| 19 | Application of Improved Particle Swarm Optimization in VRP | 2008 | 2 |
| 20 | Particle Swarm Optimization for 0/1 Knapsack Problem | 2005 | 4 |
About Yimu Ji
Yimu Ji is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Signal Processing and Information Systems, having authored 116 papers that have together received 751 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (19 papers), Video Surveillance and Tracking Methods (17 papers), Advanced Image and Video Retrieval Techniques (8 papers), Face recognition and analysis (7 papers), Network Security and Intrusion Detection (6 papers), Traffic Prediction and Management Techniques (6 papers), Anomaly Detection Techniques and Applications (6 papers) and Misinformation and Its Impacts (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (406 citations), Media Technology (61 citations), Artificial Intelligence (218 citations), Signal Processing (56 citations) and Information Systems (110 citations). Yimu Ji has collaborated with scholars based in China, Australia and Singapore. Frequent co-authors include Fei Wu, Xiao‐Yuan Jing, Shangdong Liu, Ruchuan Wang, Qinghua Huang, Debiao He, Huaqun Wang, Xiwei Dong, Chao Lan and Guo‐Ping Jiang. Their work appears in journals such as Pattern Recognition, Sensors, IEEE Signal Processing Letters, IEEE Transactions on Multimedia and Applied Sciences.
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.