Ismail Ben Ayed
Impact in
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- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
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- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Medical Image Segmentation Techniques 63
- Advanced Neural Network Applications 45
- Advanced Image and Video Retrieval Techniques 16
- Multimodal Machine Learning Applications 15
- Image and Object Detection Techniques 14
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- Domain Adaptation and Few-Shot Learning 35
- Co-authors
- José Dolz (53 shared papers)Amar Mitiche (26 shared papers)Christian Desrosiers (25 shared papers)Shuo Li (32 shared papers)Éric Granger (18 shared papers)Yuri Boykov (14 shared papers)Hoel Kervadec (11 shared papers)Meng Tang (9 shared papers)
In The Last Decade
Ismail Ben Ayed
165 papers receiving 4.5k citations
Ismail Ben Ayed's Hit Papers
Peers
Comparison fields: 5 of 150
- Computer Vision and Pattern Recognition 2.6k
- Radiology, Nuclear Medicine and Imaging 1.4k
- Neurology 361
- Media Technology 349
- Artificial Intelligence 1.2k
Countries citing papers authored by Ismail Ben Ayed
This map shows the geographic impact of Ismail Ben Ayed'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 Ismail Ben Ayed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ismail Ben Ayed more than expected).
Fields of papers citing papers by Ismail Ben Ayed
This network shows the impact of papers produced by Ismail Ben Ayed. 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 Ismail Ben Ayed. The network helps show where Ismail Ben Ayed may publish in the future.
Co-authors
The 25 scholars most cited alongside Ismail Ben Ayed, 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 183 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Boundary loss for highly unbalanced segmentation Hit paper breakdown → | 2020 | 341 |
| 2 | 2017 | 321 | |
| 3 | 2019 | 199 | |
| 4 | 2014 | 190 | |
| 5 | 2018 | 190 | |
| 6 | 2010 | 177 | |
| 7 | 2005 | 156 | |
| 8 | 2019 | 149 | |
| 9 | 2010 | 94 | |
| 10 | 2022 | 92 | |
| 11 | 2019 | 91 | |
| 12 | 2018 | 87 | |
| 13 | 2018 | 85 | |
| 14 | 2022 | 73 | |
| 15 | 2013 | 72 | |
| 16 | 2017 | 72 | |
| 17 | 2022 | 70 | |
| 18 | 2006 | 67 | |
| 19 | 2011 | 66 | |
| 20 | 2011 | 63 |
About Ismail Ben Ayed
Ismail Ben Ayed is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computational Mechanics and Media Technology, having authored 183 papers that have together received 4.7k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (63 papers), Advanced Neural Network Applications (45 papers), Domain Adaptation and Few-Shot Learning (35 papers), Sparse and Compressive Sensing Techniques (18 papers), Advanced Image and Video Retrieval Techniques (16 papers), Multimodal Machine Learning Applications (15 papers), Image and Object Detection Techniques (14 papers) and Radiomics and Machine Learning in Medical Imaging (13 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.6k citations), Radiology, Nuclear Medicine and Imaging (1.4k citations), Neurology (361 citations), Media Technology (349 citations) and Artificial Intelligence (1.2k citations). Ismail Ben Ayed has collaborated with scholars based in Canada, Spain and France. Frequent co-authors include José Dolz, Amar Mitiche, Christian Desrosiers, Shuo Li, Éric Granger, Yuri Boykov, Hoel Kervadec, Meng Tang, Kumaradevan Punithakumar and Mohamed Ben Salah. Their work appears in journals such as Medical Image Analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, IEEE Transactions on Medical Imaging and Lecture notes in computer science.
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.