Jun Lai
Impact in
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- Medical Image Segmentation Techniques
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- Reinforcement Learning in Robotics
Papers in
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- Reinforcement Learning in Robotics 8
- Artificial Intelligence in Games 4
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- Web Data Mining and Analysis 5
- Co-authors
- Lei Cao (7 shared papers)Chenxi Li (3 shared papers)Changzhan Gu (4 shared papers)Ming Ye (1 shared paper)Junfa Mao (4 shared papers)Ben Soh (4 shared papers)Zijian Shao (2 shared papers)Yongjun Meng (1 shared paper)
- Journals
- Neurocomputing (2 papers)IEEE Access (2 papers)The Computer Journal (2 papers)IEEE Open Journal of Antennas and Propagation (1 paper)Dyes and Pigments (1 paper)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Jun Lai
41 papers receiving 284 citations
Peers
Comparison fields: 5 of 86
- Computer Vision and Pattern Recognition 46
- Artificial Intelligence 68
- Aerospace Engineering 38
- Radiology, Nuclear Medicine and Imaging 30
- Human-Computer Interaction 8
Countries citing papers authored by Jun Lai
This map shows the geographic impact of Jun Lai'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 Lai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Lai more than expected).
Fields of papers citing papers by Jun Lai
This network shows the impact of papers produced by Jun Lai. 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 Lai. The network helps show where Jun Lai may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Lai, 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 54 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 26 | |
| 2 | 2020 | 25 | |
| 3 | 2022 | 21 | |
| 4 | 2017 | 20 | |
| 5 | 2018 | 19 | |
| 6 | 2014 | 16 | |
| 7 | 2023 | 15 | |
| 8 | Travel and Tourism: An Industry Primer | 2007 | 14 |
| 9 | 2020 | 13 | |
| 10 | 2022 | 13 | |
| 11 | 2009 | 12 | |
| 12 | 2017 | 12 | |
| 13 | 2023 | 9 | |
| 14 | 2022 | 8 | |
| 15 | 2019 | 7 | |
| 16 | A Method of Road Extraction from High-resolution Remote Sensing Images Based on Shape Features | 2016 | 7 |
| 17 | 2023 | 6 | |
| 18 | 2024 | 6 | |
| 19 | 2009 | 5 | |
| 20 | 2018 | 5 |
About Jun Lai
Jun Lai is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Control and Systems Engineering, having authored 54 papers that have together received 300 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (8 papers), Medical Image Segmentation Techniques (7 papers), Web Data Mining and Analysis (5 papers), Artificial Intelligence in Games (4 papers), Adaptive Dynamic Programming Control (3 papers), Data Management and Algorithms (3 papers), Antenna Design and Analysis (3 papers) and Medical Imaging Techniques and Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (46 citations), Artificial Intelligence (68 citations), Aerospace Engineering (38 citations), Radiology, Nuclear Medicine and Imaging (30 citations) and Human-Computer Interaction (8 citations). Jun Lai has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Lei Cao, Chenxi Li, Changzhan Gu, Ming Ye, Junfa Mao, Ben Soh, Zijian Shao, Yongjun Meng, Zhengan Zhang and Yitao Liao. Their work appears in journals such as Neurocomputing, IEEE Access, The Computer Journal, IEEE Open Journal of Antennas and Propagation and Dyes and Pigments.
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.