John S. DaPonte
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging
- Molecular Biology
- Economics and Econometrics
- Co-authors
- M.D. FoxC. BroadbridgeGeorge TselioudisJoseph N. VitaleMichael ClarkM. SawickiBethany M. NiedzielskiMegan Damon
- Topics
- Medical Image Segmentation Techniques (8 papers)Remote Sensing in Agriculture (5 papers)AI in cancer detection (4 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceRadiology, Nuclear Medicine and Imaging
- Journals
- IEEE Transactions on Medical ImagingPattern Recognition LettersComputerized Medical Imaging and Graphics
- Partner nations
- United States
In The Last Decade
John S. DaPonte
23 papers receiving 368 citations
Peers
Comparison fields: 5 of 87
- Computer Vision and Pattern Recognition 206
- Artificial Intelligence 137
- Radiology, Nuclear Medicine and Imaging 95
- Molecular Biology 42
- Economics and Econometrics 39
Countries citing papers authored by John S. DaPonte
This map shows the geographic impact of John S. DaPonte'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 John S. DaPonte with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John S. DaPonte more than expected).
Fields of papers citing papers by John S. DaPonte
This network shows the impact of papers produced by John S. DaPonte. 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 John S. DaPonte. The network helps show where John S. DaPonte may publish in the future.
Co-authorship network of co-authors of John S. DaPonte
This figure shows the co-authorship network connecting the top 25 collaborators of John S. DaPonte. A scholar is included among the top collaborators of John S. DaPonte based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John S. DaPonte. John S. DaPonte is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 0 | |
| 12 | 1 | |
| 13 | 8 | |
| 14 | 1 | |
| 15 | 5 | |
| 16 | 2 | |
| 17 | 1 | |
| 18 | 35 | |
| 19 | 283 | |
| 20 | 31 |
About John S. DaPonte
John S. DaPonte is a scholar working on Structural Biology, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 26 papers that have together received 397 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (8 papers), Remote Sensing in Agriculture (5 papers) and AI in cancer detection (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (206 citations), Artificial Intelligence (137 citations) and Radiology, Nuclear Medicine and Imaging (95 citations). John S. DaPonte has collaborated with scholars based in United States. Frequent co-authors include M.D. Fox, C. Broadbridge, George Tselioudis, Joseph N. Vitale, Michael Clark, M. Sawicki, Bethany M. Niedzielski, Megan Damon, David A. Katz and William B. Rossow. Their work appears in journals such as IEEE Transactions on Medical Imaging, Pattern Recognition Letters and Computerized Medical Imaging and Graphics.
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.