Ashnil Kumar
Impact in
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- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Medical Image Segmentation Techniques
- Health Informatics top 5%
Papers in
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- Image Retrieval and Classification Techniques 18
- Advanced Image and Video Retrieval Techniques 11
- Medical Image Segmentation Techniques 9
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- AI in cancer detection 16
- Co-authors
- Jinman Kim (48 shared papers)Michael Fulham (30 shared papers)Dagan Feng (39 shared papers)Lei Bi (13 shared papers)Euijoon Ahn (7 shared papers)Dagan Feng (1 shared paper)Weidong Cai (2 shared papers)Changyang Li (5 shared papers)
In The Last Decade
Ashnil Kumar
53 papers receiving 1.8k citations
Ashnil Kumar's Hit Papers
Peers
Comparison fields: 5 of 132
- Computer Vision and Pattern Recognition 693
- Health Informatics 37
- Artificial Intelligence 838
- Radiology, Nuclear Medicine and Imaging 460
- Oncology 468
Countries citing papers authored by Ashnil Kumar
This map shows the geographic impact of Ashnil Kumar'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 Ashnil Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashnil Kumar more than expected).
Fields of papers citing papers by Ashnil Kumar
This network shows the impact of papers produced by Ashnil Kumar. 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 Ashnil Kumar. The network helps show where Ashnil Kumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Ashnil Kumar, 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 | An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classification Hit paper breakdown → | 2016 | 389 |
| 2 | 2017 | 235 | |
| 3 | 2013 | 156 | |
| 4 | 2018 | 151 | |
| 5 | 2017 | 111 | |
| 6 | 2016 | 56 | |
| 7 | 2019 | 52 | |
| 8 | 2017 | 42 | |
| 9 | 2016 | 40 | |
| 10 | 2020 | 38 | |
| 11 | 2016 | 37 | |
| 12 | 2022 | 31 | |
| 13 | 2022 | 30 | |
| 14 | 2019 | 30 | |
| 15 | 2016 | 30 | |
| 16 | 2016 | 28 | |
| 17 | 2019 | 27 | |
| 18 | 2017 | 27 | |
| 19 | 2013 | 26 | |
| 20 | 2019 | 25 |
About Ashnil Kumar
Ashnil Kumar is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Oncology, having authored 54 papers that have together received 1.8k indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (18 papers), AI in cancer detection (16 papers), Advanced Image and Video Retrieval Techniques (11 papers), Medical Image Segmentation Techniques (9 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Cutaneous Melanoma Detection and Management (5 papers), COVID-19 diagnosis using AI (5 papers) and Medical Imaging Techniques and Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (693 citations), Health Informatics (37 citations), Artificial Intelligence (838 citations), Radiology, Nuclear Medicine and Imaging (460 citations) and Oncology (468 citations). Ashnil Kumar has collaborated with scholars based in Australia, China and Hong Kong. Frequent co-authors include Jinman Kim, Michael Fulham, Dagan Feng, Lei Bi, Euijoon Ahn, Dagan Feng, Weidong Cai, Changyang Li, Lingfeng Wen and Ralph Nanan. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, Computerized Medical Imaging and Graphics, IEEE Transactions on Medical Imaging, Medical Image Analysis and Clinical Otolaryngology.
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.