Vijay John
Impact in
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- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Human Pose and Action Recognition
- Image Enhancement Techniques
- Media Technology top 2%
- Advanced Image Fusion Techniques
Papers in
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- Video Surveillance and Tracking Methods 22
- Advanced Neural Network Applications 14
- Human Pose and Action Recognition 13
- Advanced Vision and Imaging 9
- Image Enhancement Techniques 9
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- Autonomous Vehicle Technology and Safety 11
- Co-authors
- Seiichi Mita (21 shared papers)Zheng Liu (14 shared papers)Bin Qi (5 shared papers)Erik Blasch (5 shared papers)Zheng Liu (2 shared papers)Emanuele Trucco (5 shared papers)S. Mita (6 shared papers)Shuo Liu (3 shared papers)
In The Last Decade
Vijay John
51 papers receiving 899 citations
Peers
Comparison fields: 5 of 88
- Computer Vision and Pattern Recognition 583
- Media Technology 148
- Human-Computer Interaction 80
- Automotive Engineering 164
- Aerospace Engineering 190
Countries citing papers authored by Vijay John
This map shows the geographic impact of Vijay John'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 Vijay John with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vijay John more than expected).
Fields of papers citing papers by Vijay John
This network shows the impact of papers produced by Vijay John. 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 Vijay John. The network helps show where Vijay John may publish in the future.
Co-authors
The 25 scholars most cited alongside Vijay John, 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 | 2014 | 83 | |
| 2 | 2015 | 83 | |
| 3 | 2016 | 73 | |
| 4 | 2015 | 58 | |
| 5 | 2010 | 57 | |
| 6 | 2017 | 57 | |
| 7 | 2016 | 46 | |
| 8 | 2017 | 40 | |
| 9 | 2019 | 38 | |
| 10 | 2020 | 30 | |
| 11 | 2018 | 29 | |
| 12 | 2020 | 27 | |
| 13 | 2016 | 26 | |
| 14 | 2021 | 24 | |
| 15 | 2016 | 20 | |
| 16 | 2013 | 17 | |
| 17 | 2014 | 16 | |
| 18 | 2017 | 16 | |
| 19 | 2018 | 15 | |
| 20 | 2022 | 14 |
About Vijay John
Vijay John is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering, Aerospace Engineering, Artificial Intelligence and Media Technology, having authored 54 papers that have together received 941 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (22 papers), Advanced Neural Network Applications (14 papers), Human Pose and Action Recognition (13 papers), Autonomous Vehicle Technology and Safety (11 papers), Advanced Vision and Imaging (9 papers), Image Enhancement Techniques (9 papers), Advanced Image Fusion Techniques (7 papers) and Infrared Target Detection Methodologies (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (583 citations), Media Technology (148 citations), Human-Computer Interaction (80 citations), Automotive Engineering (164 citations) and Aerospace Engineering (190 citations). Vijay John has collaborated with scholars based in Japan, Canada and China. Frequent co-authors include Seiichi Mita, Zheng Liu, Bin Qi, Erik Blasch, Zheng Liu, Emanuele Trucco, S. Mita, Shuo Liu, Kazue Yoneda and Hossein Tehrani. Their work appears in journals such as ACM Transactions on Multimedia Computing Communications and Applications, Information Fusion, Image and Vision Computing, Electronics and Australian Endodontic Journal.
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.