Maxime Devanne
Impact in
- Human-Computer Interaction top 5%
- Hand Gesture Recognition Systems
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- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
Papers in
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- Anomaly Detection Techniques and Applications 10
- AI in cancer detection 3
- Neural Networks and Applications 2
- Adversarial Robustness in Machine Learning 2
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- Human Pose and Action Recognition 4
- Co-authors
- Stefano Berretti (6 shared papers)Pietro Pala (2 shared papers)Hazem Wannous (2 shared papers)Mohamed Daoudi (2 shared papers)Alberto Del Bimbo (2 shared papers)Germain Forestier (13 shared papers)Jonathan Weber (14 shared papers)François Ghiringhelli (2 shared papers)
In The Last Decade
Maxime Devanne
18 papers receiving 461 citations
Peers
Comparison fields: 5 of 71
- Human-Computer Interaction 105
- Computer Vision and Pattern Recognition 288
- Artificial Intelligence 247
- Radiology, Nuclear Medicine and Imaging 113
- Signal Processing 47
Countries citing papers authored by Maxime Devanne
This map shows the geographic impact of Maxime Devanne'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 Maxime Devanne with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maxime Devanne more than expected).
Fields of papers citing papers by Maxime Devanne
This network shows the impact of papers produced by Maxime Devanne. 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 Maxime Devanne. The network helps show where Maxime Devanne may publish in the future.
Co-authors
The 25 scholars most cited alongside Maxime Devanne, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 226 | |
| 2 | 2021 | 139 | |
| 3 | 2016 | 38 | |
| 4 | 2022 | 16 | |
| 5 | 2022 | 13 | |
| 6 | 2023 | 9 | |
| 7 | 2022 | 8 | |
| 8 | 2025 | 7 | |
| 9 | 2022 | 7 | |
| 10 | 2023 | 5 | |
| 11 | 2022 | 4 | |
| 12 | 2023 | 3 | |
| 13 | 2023 | 2 | |
| 14 | 2022 | 2 | |
| 15 | 2024 | 2 | |
| 16 | 2023 | 1 | |
| 17 | 2023 | 1 | |
| 18 | 2023 | 1 | |
| 19 | 2025 | 0 | |
| 20 | 2024 | 0 |
About Maxime Devanne
Maxime Devanne is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Biomedical Engineering and Radiology, Nuclear Medicine and Imaging, having authored 23 papers that have together received 484 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (10 papers), Time Series Analysis and Forecasting (7 papers), Music and Audio Processing (5 papers), Human Pose and Action Recognition (4 papers), AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Neural Networks and Applications (2 papers) and Adversarial Robustness in Machine Learning (2 papers). The work is most often cited by research in Human-Computer Interaction (105 citations), Computer Vision and Pattern Recognition (288 citations), Artificial Intelligence (247 citations), Radiology, Nuclear Medicine and Imaging (113 citations) and Signal Processing (47 citations). Maxime Devanne has collaborated with scholars based in France, Italy and Ethiopia. Frequent co-authors include Stefano Berretti, Pietro Pala, Hazem Wannous, Mohamed Daoudi, Alberto Del Bimbo, Germain Forestier, Jonathan Weber, François Ghiringhelli, Caroline Truntzer and Valentin Dérangère. Their work appears in journals such as Knowledge and Information Systems, Artificial Intelligence in Medicine, IEEE Transactions on Cybernetics, Pattern Recognition and Computers in Biology and Medicine.
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.