Nathan D. Cahill
- Computer Vision and Pattern Recognition top 5%
- Cognitive Neuroscience top 5%
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Media Technology top 5%
- Co-authors
- Stefi A. BaumAndrew M. MichaelDarren A. NarayanChristopher KananTyler L. HayesJ. Alison NobleGajendra J. KatuwalDavid J. Hawkes
- Topics
- Medical Image Segmentation Techniques (19 papers)Remote-Sensing Image Classification (11 papers)Medical Imaging Techniques and Applications (8 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Nathan D. Cahill
62 papers receiving 956 citations
Peers
Comparison fields: 5 of 127
- Computer Vision and Pattern Recognition 311
- Cognitive Neuroscience 285
- Artificial Intelligence 189
- Radiology, Nuclear Medicine and Imaging 170
- Media Technology 123
Countries citing papers authored by Nathan D. Cahill
This map shows the geographic impact of Nathan D. Cahill'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 Nathan D. Cahill with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan D. Cahill more than expected).
Fields of papers citing papers by Nathan D. Cahill
This network shows the impact of papers produced by Nathan D. Cahill. 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 Nathan D. Cahill. The network helps show where Nathan D. Cahill may publish in the future.
Co-authorship network of co-authors of Nathan D. Cahill
This figure shows the co-authorship network connecting the top 25 collaborators of Nathan D. Cahill. A scholar is included among the top collaborators of Nathan D. Cahill 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 Nathan D. Cahill. Nathan D. Cahill is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 10 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 98 | |
| 9 | 25 | |
| 10 | 88 | |
| 11 | 40 | |
| 12 | 27 | |
| 13 | 42 | |
| 14 | 34 | |
| 15 | 6 | |
| 16 | 29 | |
| 17 | 1 | |
| 18 | 40 | |
| 19 | 46 | |
| 20 | 19 |
About Nathan D. Cahill
Nathan D. Cahill is a scholar working on Theoretical Computer Science, Computer Vision and Pattern Recognition and Media Technology, having authored 67 papers that have together received 1.0k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (19 papers), Remote-Sensing Image Classification (11 papers) and Medical Imaging Techniques and Applications (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (311 citations), Cognitive Neuroscience (285 citations) and Media Technology (123 citations). Nathan D. Cahill has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Stefi A. Baum, Andrew M. Michael, Darren A. Narayan, Christopher Kanan, Tyler L. Hayes, J. Alison Noble, Gajendra J. Katuwal, David J. Hawkes, David W. Messinger and Tonya White. Their work appears in journals such as PLoS ONE, Monthly Notices of the Royal Astronomical Society and Schizophrenia Bulletin.
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.