Mohamed Tajine
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Computational Theory and Mathematics
- Radiology, Nuclear Medicine and Imaging
- Computational Mechanics
- Co-authors
- David ElizondoChristian RonseLuc SolerGrégoire MalandainVincent AgnusGrégory KucherovEmile FieslerJerzy Korczak
- Topics
- Digital Image Processing Techniques (10 papers)Medical Image Segmentation Techniques (9 papers)Neural Networks and Applications (4 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignComputational Theory and Mathematics
- Partner nations
- FranceSwitzerland
In The Last Decade
Mohamed Tajine
18 papers receiving 108 citations
Peers
Comparison fields: 5 of 30
- Computer Vision and Pattern Recognition 84
- Artificial Intelligence 44
- Computational Theory and Mathematics 26
- Radiology, Nuclear Medicine and Imaging 15
- Computational Mechanics 13
Countries citing papers authored by Mohamed Tajine
This map shows the geographic impact of Mohamed Tajine'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 Mohamed Tajine with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohamed Tajine more than expected).
Fields of papers citing papers by Mohamed Tajine
This network shows the impact of papers produced by Mohamed Tajine. 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 Mohamed Tajine. The network helps show where Mohamed Tajine may publish in the future.
Co-authorship network of co-authors of Mohamed Tajine
This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed Tajine. A scholar is included among the top collaborators of Mohamed Tajine 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 Mohamed Tajine. Mohamed Tajine 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 | 1 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 3 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 23 | |
| 10 | 6 | |
| 11 | 7 | |
| 12 | 11 | |
| 13 | 4 | |
| 14 | 5 | |
| 15 | 18 | |
| 16 | 7 | |
| 17 | 14 | |
| 18 | An approach to discretization based on the Hausdorff metric | 3 |
| 19 | 2 | |
| 20 | 5 |
About Mohamed Tajine
Mohamed Tajine is a scholar working on Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Numerical Analysis, having authored 20 papers that have together received 119 indexed citations. Recurring topics across this work include Digital Image Processing Techniques (10 papers), Medical Image Segmentation Techniques (9 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (84 citations), Computer Graphics and Computer-Aided Design (6 citations) and Computational Theory and Mathematics (26 citations). Mohamed Tajine has collaborated with scholars based in France and Switzerland. Frequent co-authors include David Elizondo, Christian Ronse, Luc Soler, Grégoire Malandain, Vincent Agnus, Grégory Kucherov, Emile Fiesler, Jerzy Korczak, Minh-Son Phan and Stéphane Nicolau. Their work appears in journals such as Artificial Intelligence, Neurocomputing and Neural Networks.
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.