Junlan Jin
Impact in
- Media Technology top 5%
- Remote-Sensing Image Classification
- Advanced Image Fusion Techniques
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- Human Pose and Action Recognition
- Image Enhancement Techniques
Papers in
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- Human Pose and Action Recognition 6
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- Anomaly Detection Techniques and Applications 6
- Co-authors
- Kai Hu (8 shared papers)Min Xia (4 shared papers)Liguo Weng (5 shared papers)Ming Qian (1 shared paper)Yonghong Zhang (1 shared paper)Qingfeng Xia (2 shared papers)Fei Zheng (2 shared papers)Marc Vanderhaeghen (1 shared paper)
- Journals
- Applied Sciences (3 papers)Sensors (1 paper)Multimedia Systems (1 paper)Annalen der Physik (1 paper)International Journal of Applied Earth Observation and Geoinformation (1 paper)
- Partner nations
- ChinaUnited Kingdom
In The Last Decade
Junlan Jin
9 papers receiving 314 citations
Peers
Comparison fields: 5 of 64
- Media Technology 114
- Computer Vision and Pattern Recognition 186
- Atmospheric Science 60
- Artificial Intelligence 95
- Ocean Engineering 31
Countries citing papers authored by Junlan Jin
This map shows the geographic impact of Junlan Jin'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 Junlan Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junlan Jin more than expected).
Fields of papers citing papers by Junlan Jin
This network shows the impact of papers produced by Junlan Jin. 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 Junlan Jin. The network helps show where Junlan Jin may publish in the future.
Co-authors
The 22 scholars most cited alongside Junlan Jin, 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 | 2021 | 95 | |
| 2 | 2022 | 89 | |
| 3 | 2022 | 56 | |
| 4 | 2022 | 25 | |
| 5 | 2022 | 23 | |
| 6 | 2023 | 14 | |
| 7 | 2021 | 12 | |
| 8 | 2022 | 9 | |
| 9 | 2021 | 3 | |
| 10 | 2022 | 0 |
About Junlan Jin
Junlan Jin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, Computer Networks and Communications and Control and Systems Engineering, having authored 10 papers that have together received 326 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (6 papers), Anomaly Detection Techniques and Applications (6 papers), Gait Recognition and Analysis (5 papers), Advanced Chemical Sensor Technologies (1 paper), Remote-Sensing Image Classification (1 paper), Radiation Detection and Scintillator Technologies (1 paper), Remote Sensing and Land Use (1 paper) and Adaptive Dynamic Programming Control (1 paper). The work is most often cited by research in Media Technology (114 citations), Computer Vision and Pattern Recognition (186 citations), Atmospheric Science (60 citations), Artificial Intelligence (95 citations) and Ocean Engineering (31 citations). Junlan Jin has collaborated with scholars based in China and United Kingdom. Frequent co-authors include Kai Hu, Min Xia, Liguo Weng, Ming Qian, Yonghong Zhang, Qingfeng Xia, Fei Zheng, Marc Vanderhaeghen, V. V. Flambaum and P. G. Thirolf. Their work appears in journals such as Applied Sciences, Sensors, Multimedia Systems, Annalen der Physik and International Journal of Applied Earth Observation and Geoinformation.
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.