Jun Lü
Impact in
- Radiation top 2%
- Advanced Radiotherapy Techniques
- Media Technology top 5%
- Remote-Sensing Image Classification
Papers in
-
- Advanced SAR Imaging Techniques 10
- Synthetic Aperture Radar (SAR) Applications and Techniques 7
- Co-authors
- Gangyao Kuang (12 shared papers)Nong Sang (3 shared papers)Лей Ши (9 shared papers)Ganggang Dong (3 shared papers)Na Wang (3 shared papers)Lingjun Zhao (1 shared paper)Elisabeth Weiss (5 shared papers)Geoffrey D. Hugo (4 shared papers)
- Journals
- Medical Physics (6 papers)Computational Statistics & Data Analysis (4 papers)Forest Ecology and Management (4 papers)IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2 papers)PLoS ONE (2 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Jun Lü
116 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 102
- Radiation 279
- Media Technology 99
- Aerospace Engineering 270
- Nature and Landscape Conservation 93
- Computer Vision and Pattern Recognition 201
Countries citing papers authored by Jun Lü
This map shows the geographic impact of Jun Lü'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 Lü with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Lü more than expected).
Fields of papers citing papers by Jun Lü
This network shows the impact of papers produced by Jun Lü. 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 Lü. The network helps show where Jun Lü may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Lü, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 127 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 152 | |
| 2 | 2007 | 110 | |
| 3 | 2016 | 97 | |
| 4 | 2014 | 80 | |
| 5 | 2013 | 74 | |
| 6 | 2018 | 74 | |
| 7 | 2015 | 70 | |
| 8 | 2000 | 53 | |
| 9 | 2014 | 49 | |
| 10 | 2016 | 40 | |
| 11 | 2021 | 37 | |
| 12 | 2021 | 35 | |
| 13 | 2011 | 34 | |
| 14 | 2015 | 30 | |
| 15 | 2017 | 29 | |
| 16 | 2020 | 29 | |
| 17 | 2017 | 28 | |
| 18 | 2015 | 25 | |
| 19 | 2017 | 25 | |
| 20 | 2022 | 23 |
About Jun Lü
Jun Lü is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition, Statistics and Probability, Radiation and Media Technology, having authored 127 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (10 papers), Advanced SAR Imaging Techniques (10 papers), Forest ecology and management (9 papers), Smart Agriculture and AI (9 papers), Statistical Methods and Inference (8 papers), Remote-Sensing Image Classification (7 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (7 papers) and Advanced Statistical Methods and Models (7 papers). The work is most often cited by research in Radiation (279 citations), Media Technology (99 citations), Aerospace Engineering (270 citations), Nature and Landscape Conservation (93 citations) and Computer Vision and Pattern Recognition (201 citations). Jun Lü has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Gangyao Kuang, Nong Sang, Лей Ши, Ganggang Dong, Na Wang, Lingjun Zhao, Elisabeth Weiss, Geoffrey D. Hugo, Paul Keall and Boli Xiong. Their work appears in journals such as Medical Physics, Computational Statistics & Data Analysis, Forest Ecology and Management, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and PLoS ONE.
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.