Jun Kong
Impact in
- Biophysics top 0.5%
- Cell Image Analysis Techniques
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- Digital Imaging for Blood Diseases
- Medical Image Segmentation Techniques
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
Papers in
-
- AI in cancer detection 43
- Semantic Web and Ontologies 16
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- Medical Image Segmentation Techniques 28
- Advanced Image and Video Retrieval Techniques 14
- Co-authors
- Joel Saltz (38 shared papers)Daniel J. Brat (36 shared papers)Metin N. Gürcan (17 shared papers)Olcay Sertel (13 shared papers)Lee Cooper (28 shared papers)Fusheng Wang (60 shared papers)Tahsin Kurç (35 shared papers)Ümit V. Çatalyürek (9 shared papers)
- Journals
- Journal of Visual Languages & Computing (7 papers)Bioinformatics (5 papers)Computers in Biology and Medicine (4 papers)Journal of Pathology Informatics (3 papers)Neuro-Oncology (3 papers)
- Partner nations
- United StatesChinaBrazil
In The Last Decade
Jun Kong
221 papers receiving 3.9k citations
Peers
Comparison fields: 5 of 177
- Biophysics 458
- Computer Vision and Pattern Recognition 976
- Artificial Intelligence 1.4k
- Software 173
- Health Informatics 48
Countries citing papers authored by Jun Kong
This map shows the geographic impact of Jun Kong'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 Kong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Kong more than expected).
Fields of papers citing papers by Jun Kong
This network shows the impact of papers produced by Jun Kong. 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 Kong. The network helps show where Jun Kong may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Kong, 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 235 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 182 | |
| 2 | 2008 | 176 | |
| 3 | 2008 | 168 | |
| 4 | 2013 | 158 | |
| 5 | 2013 | 139 | |
| 6 | 2008 | 126 | |
| 7 | 2013 | 90 | |
| 8 | 2015 | 78 | |
| 9 | 2012 | 77 | |
| 10 | 2014 | 74 | |
| 11 | 2006 | 60 | |
| 12 | 2005 | 59 | |
| 13 | 2017 | 57 | |
| 14 | 2009 | 57 | |
| 15 | 2011 | 54 | |
| 16 | 2006 | 53 | |
| 17 | 2014 | 53 | |
| 18 | 2008 | 52 | |
| 19 | 2013 | 51 | |
| 20 | 2010 | 50 |
About Jun Kong
Jun Kong is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Biophysics, Computer Networks and Communications and Information Systems, having authored 235 papers that have together received 4.0k indexed citations. Recurring topics across this work include AI in cancer detection (43 papers), Cell Image Analysis Techniques (31 papers), Medical Image Segmentation Techniques (28 papers), Model-Driven Software Engineering Techniques (21 papers), Radiomics and Machine Learning in Medical Imaging (17 papers), Data Management and Algorithms (16 papers), Semantic Web and Ontologies (16 papers) and Advanced Image and Video Retrieval Techniques (14 papers). The work is most often cited by research in Biophysics (458 citations), Computer Vision and Pattern Recognition (976 citations), Artificial Intelligence (1.4k citations), Software (173 citations) and Health Informatics (48 citations). Jun Kong has collaborated with scholars based in United States, China and Brazil. Frequent co-authors include Joel Saltz, Daniel J. Brat, Metin N. Gürcan, Olcay Sertel, Lee Cooper, Fusheng Wang, Tahsin Kurç, Ümit V. Çatalyürek, Joel H. Saltz and George Teodoro. Their work appears in journals such as Journal of Visual Languages & Computing, Bioinformatics, Computers in Biology and Medicine, Journal of Pathology Informatics and Neuro-Oncology.
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.