Driss Mammass
- Computer Vision and Pattern Recognition top 10%
- Computer Science Applications top 5%
- Artificial Intelligence top 10%
- Plant Science
- Media Technology top 5%
- Co-authors
- Youssef Es-SaadyHassan DouziOlivier LézorayAbderrahim ElmoatazMustapha AmrouchStéphane NicolasMohamed El HajjiDriss Aboutajdine
- Topics
- Handwritten Text Recognition Techniques (10 papers)Remote-Sensing Image Classification (9 papers)Image Retrieval and Classification Techniques (7 papers)
In The Last Decade
Driss Mammass
53 papers receiving 420 citations
Peers
Comparison fields: 5 of 84
- Computer Vision and Pattern Recognition 137
- Computer Science Applications 116
- Artificial Intelligence 95
- Plant Science 93
- Media Technology 68
Countries citing papers authored by Driss Mammass
This map shows the geographic impact of Driss Mammass'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 Driss Mammass with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Driss Mammass more than expected).
Fields of papers citing papers by Driss Mammass
This network shows the impact of papers produced by Driss Mammass. 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 Driss Mammass. The network helps show where Driss Mammass may publish in the future.
Co-authorship network of co-authors of Driss Mammass
This figure shows the co-authorship network connecting the top 25 collaborators of Driss Mammass. A scholar is included among the top collaborators of Driss Mammass 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 Driss Mammass. Driss Mammass is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 60 | |
| 2 | 12 | |
| 3 | 7 | |
| 4 | Identifying and tracking learning styles in MOOCs: A neural networks approach | 15 |
| 5 | 66 | |
| 6 | 5 | |
| 7 | 4 | |
| 8 | 4 | |
| 9 | 9 | |
| 10 | 3 | |
| 11 | Handwritten Tifinagh Character Recognition Using Baselines Detection Features | 7 |
| 12 | 7 | |
| 13 | 12 | |
| 14 | 1 | |
| 15 | 6 | |
| 16 | 12 | |
| 17 | Image and Signal Processing - 3rd International Conference, ICISP 2008, Cherbourg-Octeville, France, July 1-3, 2008, Proceedings | 7 |
| 18 | Proceedings of the 3rd international conference on Image and Signal Processing | 4 |
| 19 | An automatic system for urban road extraction from satellite and aerial images | 2 |
| 20 | 5 |
About Driss Mammass
Driss Mammass is a scholar working on Media Technology, Computer Science Applications and Computer Vision and Pattern Recognition, having authored 59 papers that have together received 452 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (10 papers), Remote-Sensing Image Classification (9 papers) and Image Retrieval and Classification Techniques (7 papers). The work is most often cited by research in Computer Science Applications (116 citations), Media Technology (68 citations) and Computer Vision and Pattern Recognition (137 citations). Driss Mammass has collaborated with scholars based in Morocco, France and Canada. Frequent co-authors include Youssef Es-Saady, Hassan Douzi, Olivier Lézoray, Abderrahim Elmoataz, Mustapha Amrouch, Stéphane Nicolas, Mohamed El Hajji, Driss Aboutajdine, Alamin Mansouri and Gaëtan Le Goïc. Their work appears in journals such as Lecture notes in computer science, Education and Information Technologies and The Visual Computer.
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.