Camille Kurtz
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Media Technology top 5%
- Ecology
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Nicolas PassatPierre GançarskiAnne PuissantDaniel L. RubinChristopher F. BeaulieuFrançois PetitjeanLaurent WendlingSandy Napel
- Topics
- Image Retrieval and Classification Techniques (18 papers)Advanced Image and Video Retrieval Techniques (17 papers)AI in cancer detection (7 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingIEEE Transactions on Medical Imaging
- Partner nations
- FranceUnited StatesGermany
In The Last Decade
Camille Kurtz
40 papers receiving 674 citations
Peers
Comparison fields: 5 of 88
- Computer Vision and Pattern Recognition 219
- Artificial Intelligence 130
- Media Technology 119
- Ecology 115
- Radiology, Nuclear Medicine and Imaging 104
Countries citing papers authored by Camille Kurtz
This map shows the geographic impact of Camille Kurtz'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 Camille Kurtz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Camille Kurtz more than expected).
Fields of papers citing papers by Camille Kurtz
This network shows the impact of papers produced by Camille Kurtz. 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 Camille Kurtz. The network helps show where Camille Kurtz may publish in the future.
Co-authorship network of co-authors of Camille Kurtz
This figure shows the co-authorship network connecting the top 25 collaborators of Camille Kurtz. A scholar is included among the top collaborators of Camille Kurtz 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 Camille Kurtz. Camille Kurtz 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 | 0 | |
| 3 | 25 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 9 | |
| 11 | 21 | |
| 12 | 11 | |
| 13 | 62 | |
| 14 | 44 | |
| 15 | 33 | |
| 16 | 21 | |
| 17 | A hierarchical semantic-based distance for nominal histogram comparison | 7 |
| 18 | 11 | |
| 19 | 38 | |
| 20 | 49 |
About Camille Kurtz
Camille Kurtz is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 47 papers that have together received 703 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (18 papers), Advanced Image and Video Retrieval Techniques (17 papers) and AI in cancer detection (7 papers). The work is most often cited by research in Media Technology (119 citations), Computer Vision and Pattern Recognition (219 citations) and Health Informatics (12 citations). Camille Kurtz has collaborated with scholars based in France, United States and Germany. Frequent co-authors include Nicolas Passat, Pierre Gançarski, Anne Puissant, Daniel L. Rubin, Christopher F. Beaulieu, François Petitjean, Laurent Wendling, Sandy Napel, André Stumpf and Jean‐Philippe Malet. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Transactions on Medical Imaging.
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.