Jun Che
Impact in
- Plant Science top 10%
- Smart Agriculture and AI
- Date Palm Research Studies
- Plant Disease Management Techniques
- Analytical Chemistry top 10%
- Spectroscopy and Chemometric Analyses
Papers in
-
- Robotic Path Planning Algorithms 3
- Optical measurement and interference techniques 2
-
- Robotics and Sensor-Based Localization 4
- Infrared Target Detection Methodologies 1
- Co-authors
- Xiaojun Jin (3 shared papers)Yong Chen (1 shared paper)Yanxia Sun (2 shared papers)Jialin Yu (1 shared paper)Muthukumar Bagavathiannan (1 shared paper)Mingming Zhu (1 shared paper)Shuai Li (1 shared paper)Yuelei Xu (1 shared paper)
- Journals
- Remote Sensing (1 paper)IEEE Access (1 paper)Scientific Reports (1 paper)Pest Management Science (1 paper)Beijing Hangkong Hangtian Daxue xuebao (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Jun Che
14 papers receiving 373 citations
Peers
Comparison fields: 5 of 63
- Plant Science 252
- Analytical Chemistry 59
- Media Technology 46
- Computer Vision and Pattern Recognition 90
- Ecology 51
Countries citing papers authored by Jun Che
This map shows the geographic impact of Jun Che'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 Jun Che with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Che more than expected).
Fields of papers citing papers by Jun Che
This network shows the impact of papers produced by Jun Che. 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 Jun Che. The network helps show where Jun Che may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Che, 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 | 178 | |
| 2 | 2022 | 99 | |
| 3 | 2018 | 39 | |
| 4 | 2021 | 25 | |
| 5 | 2015 | 14 | |
| 6 | 2015 | 13 | |
| 7 | 2015 | 5 | |
| 8 | 2014 | 4 | |
| 9 | 2021 | 3 | |
| 10 | 2025 | 1 | |
| 11 | 2015 | 1 | |
| 12 | 2012 | 1 | |
| 13 | 2016 | 1 | |
| 14 | 2012 | 1 |
About Jun Che
Jun Che is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Electrical and Electronic Engineering, Computer Networks and Communications and Mechanical Engineering, having authored 14 papers that have together received 385 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (4 papers), Robotic Path Planning Algorithms (3 papers), Optical measurement and interference techniques (2 papers), Advanced Measurement and Detection Methods (2 papers), Smart Agriculture and AI (2 papers), Advanced Image Fusion Techniques (1 paper), Date Palm Research Studies (1 paper) and Infrared Target Detection Methodologies (1 paper). The work is most often cited by research in Plant Science (252 citations), Analytical Chemistry (59 citations), Media Technology (46 citations), Computer Vision and Pattern Recognition (90 citations) and Ecology (51 citations). Jun Che has collaborated with scholars based in China and United States. Frequent co-authors include Xiaojun Jin, Yong Chen, Yanxia Sun, Jialin Yu, Yong Chen, Muthukumar Bagavathiannan, Mingming Zhu, Shuai Li, Yuelei Xu and Shiping Ma. Their work appears in journals such as Remote Sensing, IEEE Access, Scientific Reports, Pest Management Science and Beijing Hangkong Hangtian Daxue xuebao.
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.