Aicha Majda
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Face and Expression Recognition
Papers in
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- Face recognition and analysis 7
- Face and Expression Recognition 5
- Medical Image Segmentation Techniques 3
- Advanced Neural Network Applications 3
- Co-authors
- Arsalane Zarghili (13 shared papers)Najia Es-Sbai (1 shared paper)Nikola S. Nikolov (3 shared papers)Rachid Aalouane (3 shared papers)Djamal Merad (2 shared papers)Khalid Zenkouar (1 shared paper)
- Journals
- Journal of King Saud University - Computer and Information Sciences (2 papers)Intelligent Systems with Applications (1 paper)Machine Vision and Applications (1 paper)IET Image Processing (1 paper)International Journal of Intelligent Systems Technologies and Applications (2 papers)
In The Last Decade
Aicha Majda
23 papers receiving 358 citations
Peers
Comparison fields: 5 of 88
- Radiology, Nuclear Medicine and Imaging 177
- Computer Vision and Pattern Recognition 121
- Health Informatics 5
- Neurology 27
- Artificial Intelligence 96
Countries citing papers authored by Aicha Majda
This map shows the geographic impact of Aicha Majda'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 Aicha Majda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aicha Majda more than expected).
Fields of papers citing papers by Aicha Majda
This network shows the impact of papers produced by Aicha Majda. 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 Aicha Majda. The network helps show where Aicha Majda may publish in the future.
Co-authors
The 6 scholars most cited alongside Aicha Majda, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 229 | |
| 2 | 2017 | 40 | |
| 3 | 2021 | 30 | |
| 4 | 2019 | 10 | |
| 5 | 2019 | 9 | |
| 6 | 2017 | 9 | |
| 7 | 2016 | 8 | |
| 8 | 2021 | 5 | |
| 9 | 2019 | 5 | |
| 10 | 2019 | 5 | |
| 11 | 2016 | 4 | |
| 12 | 2020 | 3 | |
| 13 | 2020 | 3 | |
| 14 | 2019 | 3 | |
| 15 | 2021 | 3 | |
| 16 | 2011 | 2 | |
| 17 | 2017 | 2 | |
| 18 | 2024 | 2 | |
| 19 | 2019 | 2 | |
| 20 | 2018 | 2 |
About Aicha Majda
Aicha Majda is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Experimental and Cognitive Psychology, having authored 26 papers that have together received 380 indexed citations. Recurring topics across this work include Face recognition and analysis (7 papers), Face and Expression Recognition (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Brain Tumor Detection and Classification (3 papers), Autism Spectrum Disorder Research (3 papers), Medical Image Segmentation Techniques (3 papers), Advanced Neural Network Applications (3 papers) and COVID-19 diagnosis using AI (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (177 citations), Computer Vision and Pattern Recognition (121 citations), Health Informatics (5 citations), Neurology (27 citations) and Artificial Intelligence (96 citations). Aicha Majda has collaborated with scholars based in Morocco, Ireland and France. Frequent co-authors include Arsalane Zarghili, Najia Es-Sbai, Nikola S. Nikolov, Rachid Aalouane, Djamal Merad and Khalid Zenkouar. Their work appears in journals such as Journal of King Saud University - Computer and Information Sciences, Intelligent Systems with Applications, Machine Vision and Applications, IET Image Processing and International Journal of Intelligent Systems Technologies and Applications.
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.