E. S. Gelsema
Impact in
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- Context-Aware Activity Recognition Systems
- Digital Imaging for Blood Diseases
- Structural Biology top 10%
Papers in
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- Digital Imaging for Blood Diseases 14
- Image Retrieval and Classification Techniques 4
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- AI in cancer detection 11
- Co-authors
- Jifke F. Veenland (5 shared papers)Kourosh Kiani (2 shared papers)Chris J. Snijders (2 shared papers)Laveen N. Kanal (4 shared papers)Daniel Q. Naiman (1 shared paper)Arnaud Beckers (9 shared papers)J. L. Grashuis (6 shared papers)W.C. de Bruijn (9 shared papers)
- Journals
- Methods of Information in Medicine (7 papers)Journal of Microscopy (7 papers)Pattern Recognition (7 papers)Pattern Recognition Letters (6 papers)Cytometry (4 papers)
- Partner nations
- NetherlandsUnited StatesSwitzerland
In The Last Decade
E. S. Gelsema
67 papers receiving 839 citations
Peers
Comparison fields: 5 of 160
- Computer Vision and Pattern Recognition 214
- Structural Biology 14
- Biophysics 55
- Orthopedics and Sports Medicine 64
- Artificial Intelligence 196
Countries citing papers authored by E. S. Gelsema
This map shows the geographic impact of E. S. Gelsema'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 E. S. Gelsema with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites E. S. Gelsema more than expected).
Fields of papers citing papers by E. S. Gelsema
This network shows the impact of papers produced by E. S. Gelsema. 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 E. S. Gelsema. The network helps show where E. S. Gelsema may publish in the future.
Co-authors
The 25 scholars most cited alongside E. S. Gelsema, 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 71 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1988 | 87 | |
| 2 | 1999 | 79 | |
| 3 | 1996 | 64 | |
| 4 | 1997 | 61 | |
| 5 | 1997 | 57 | |
| 6 | 1974 | 37 | |
| 7 | 1998 | 33 | |
| 8 | 2003 | 29 | |
| 9 | 1998 | 28 | |
| 10 | 1983 | 26 | |
| 11 | 1964 | 24 | |
| 12 | 1992 | 24 | |
| 13 | 1995 | 24 | |
| 14 | 1980 | 19 | |
| 15 | 1978 | 18 | |
| 16 | 1964 | 18 | |
| 17 | 1995 | 15 | |
| 18 | 2000 | 14 | |
| 19 | 1994 | 14 | |
| 20 | 1958 | 14 |
About E. S. Gelsema
E. S. Gelsema is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Surfaces, Coatings and Films, Biophysics and Radiation, having authored 71 papers that have together received 898 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (14 papers), AI in cancer detection (11 papers), Electron and X-Ray Spectroscopy Techniques (10 papers), Cell Image Analysis Techniques (8 papers), X-ray Spectroscopy and Fluorescence Analysis (5 papers), Nuclear Physics and Applications (4 papers), Image Retrieval and Classification Techniques (4 papers) and Hemodynamic Monitoring and Therapy (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (214 citations), Structural Biology (14 citations), Biophysics (55 citations), Orthopedics and Sports Medicine (64 citations) and Artificial Intelligence (196 citations). E. S. Gelsema has collaborated with scholars based in Netherlands, United States and Switzerland. Frequent co-authors include Jifke F. Veenland, Kourosh Kiani, Chris J. Snijders, Laveen N. Kanal, Daniel Q. Naiman, Arnaud Beckers, J. L. Grashuis, W.C. de Bruijn, Guinevere F. Eden and M. R. Halie. Their work appears in journals such as Methods of Information in Medicine, Journal of Microscopy, Pattern Recognition, Pattern Recognition Letters and Cytometry.
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.