Junlan Jin
Impact in
- Media Technology top 5%
- Remote-Sensing Image Classification
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- Human Pose and Action Recognition
- Image Enhancement Techniques
- Advanced Neural Network Applications
- Context-Aware Activity Recognition Systems
Papers in
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- Human Pose and Action Recognition 6
- Image Enhancement Techniques 1
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- Remote-Sensing Image Classification 1
- Co-authors
- Kai Hu (8 shared papers)Min Xia (4 shared papers)Liguo Weng (5 shared papers)Qingfeng Xia (2 shared papers)Yonghong Zhang (1 shared paper)Ming Qian (1 shared paper)Fei Zheng (2 shared papers)Mikhail Gorchtein (1 shared paper)
- Journals
- Applied Sciences (3 papers)Sensors (1 paper)International Journal of Applied Earth Observation and Geoinformation (1 paper)Artificial Intelligence Review (1 paper)Annalen der Physik (1 paper)
- Partner nations
- ChinaUnited Kingdom
In The Last Decade
Junlan Jin
9 papers receiving 350 citations
Peers
Comparison fields: 5 of 40
- Media Technology 91
- Computer Vision and Pattern Recognition 206
- Ocean Engineering 23
- Artificial Intelligence 20
- Aerospace Engineering 14
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 | 2022 | 101 | |
| 2 | 2021 | 96 | |
| 3 | 2022 | 59 | |
| 4 | 2022 | 27 | |
| 5 | 2022 | 24 | |
| 6 | 2023 | 18 | |
| 7 | 2021 | 15 | |
| 8 | 2022 | 10 | |
| 9 | 2021 | 5 | |
| 10 | 2022 | 0 |
About Junlan Jin
Junlan Jin is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Ocean Engineering, Nuclear and High Energy Physics and Artificial Intelligence, having authored 10 papers that have together received 355 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (6 papers), Underwater Vehicles and Communication Systems (1 paper), Image Enhancement Techniques (1 paper), Reinforcement Learning in Robotics (1 paper), Maritime Navigation and Safety (1 paper), Remote-Sensing Image Classification (1 paper), High-Energy Particle Collisions Research (1 paper) and Quantum Chromodynamics and Particle Interactions (1 paper). The work is most often cited by research in Media Technology (91 citations), Computer Vision and Pattern Recognition (206 citations), Ocean Engineering (23 citations), Artificial Intelligence (20 citations) and Aerospace Engineering (14 citations). Junlan Jin has collaborated with scholars based in China and United Kingdom. Frequent co-authors include Kai Hu, Min Xia, Liguo Weng, Qingfeng Xia, Yonghong Zhang, Ming Qian, Fei Zheng, Mikhail Gorchtein, Adriana Pálffy and P. G. Thirolf. Their work appears in journals such as Applied Sciences, Sensors, International Journal of Applied Earth Observation and Geoinformation, Artificial Intelligence Review and Annalen der Physik.
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.