Stéphane Canu
Impact in
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- Face and Expression Recognition
- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Neurology top 2%
- Brain Tumor Detection and Classification
Papers in
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- Neural Networks and Applications 16
- Natural Language Processing Techniques 7
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- Face and Expression Recognition 13
- Advanced Neural Network Applications 8
- Co-authors
- Su Ruan (9 shared papers)Tongxue Zhou (8 shared papers)Yves Grandvalet (7 shared papers)Alain Rakotomamonjy (10 shared papers)Gilles Gasso (14 shared papers)Alex Smola (3 shared papers)Cheng Soon Ong (2 shared papers)Pierre Véra (4 shared papers)
In The Last Decade
Stéphane Canu
88 papers receiving 2.5k citations
Stéphane Canu's Hit Papers
Peers
Comparison fields: 5 of 161
- Computer Vision and Pattern Recognition 1.1k
- Neurology 316
- Artificial Intelligence 1.1k
- Media Technology 156
- Signal Processing 182
Countries citing papers authored by Stéphane Canu
This map shows the geographic impact of Stéphane Canu'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 Stéphane Canu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stéphane Canu more than expected).
Fields of papers citing papers by Stéphane Canu
This network shows the impact of papers produced by Stéphane Canu. 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 Stéphane Canu. The network helps show where Stéphane Canu may publish in the future.
Co-authors
The 25 scholars most cited alongside Stéphane Canu, 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 93 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A review: Deep learning for medical image segmentation using multi-modality fusion Hit paper breakdown → | 2019 | 417 |
| 2 | 2009 | 208 | |
| 3 | 2007 | 195 | |
| 4 | 2021 | 141 | |
| 5 | 2004 | 131 | |
| 6 | 2003 | 106 | |
| 7 | Adaptive Scaling for Feature Selection in SVMs | 2002 | 98 |
| 8 | 2005 | 97 | |
| 9 | 1997 | 91 | |
| 10 | 2013 | 67 | |
| 11 | 2011 | 64 | |
| 12 | 2015 | 57 | |
| 13 | Support Vector Machines with a Reject Option | 2008 | 54 |
| 14 | An approach to water supply clusters by semi-supervised learning | 2010 | 51 |
| 15 | 2006 | 44 | |
| 16 | 2012 | 41 | |
| 17 | 1987 | 40 | |
| 18 | 2000 | 40 | |
| 19 | 2021 | 40 | |
| 20 | Frames, Reproducing Kernels, Regularization and Learning | 2005 | 39 |
About Stéphane Canu
Stéphane Canu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Statistics and Probability and Control and Systems Engineering, having authored 93 papers that have together received 2.7k indexed citations. Recurring topics across this work include Neural Networks and Applications (16 papers), Face and Expression Recognition (13 papers), Sparse and Compressive Sensing Techniques (12 papers), Statistical Methods and Inference (8 papers), Advanced Neural Network Applications (8 papers), Fault Detection and Control Systems (7 papers), Natural Language Processing Techniques (7 papers) and Brain Tumor Detection and Classification (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Neurology (316 citations), Artificial Intelligence (1.1k citations), Media Technology (156 citations) and Signal Processing (182 citations). Stéphane Canu has collaborated with scholars based in France, Austria and Germany. Frequent co-authors include Su Ruan, Tongxue Zhou, Yves Grandvalet, Alain Rakotomamonjy, Gilles Gasso, Alex Smola, Cheng Soon Ong, Pierre Véra, Francis Bach and Xavier Mary. Their work appears in journals such as Neurocomputing, IEEE Transactions on Image Processing, Journal of Machine Learning Research, IEEE Transactions on Intelligent Transportation Systems and Journal of Multivariate Analysis.
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.