Arthur Douillard
Impact in
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- Multimodal Machine Learning Applications
- Advanced Neural Network Applications
- Human Pose and Action Recognition
- Advanced Image and Video Retrieval Techniques
- Artificial Intelligence top 10%
- Domain Adaptation and Few-Shot Learning
- Machine Learning and ELM
- Text and Document Classification Technologies
Papers in
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- Multimodal Machine Learning Applications 5
- Advanced Neural Network Applications 4
- Image Enhancement Techniques 1
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- Domain Adaptation and Few-Shot Learning 5
- Co-authors
- Matthieu Cord (4 shared papers)Alexandre Ramé (2 shared papers)Guillaume Couairon (1 shared paper)Tuan-Hung Vu (1 shared paper)Fabio Cermelli (1 shared paper)Patrick Pérez (1 shared paper)Arnaud Dapogny (1 shared paper)Thomas Robert (2 shared papers)
- Journals
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2 papers)arXiv (Cornell University) (3 papers)
In The Last Decade
Arthur Douillard
7 papers receiving 209 citations
Arthur Douillard's Hit Papers
Peers
Comparison fields: 5 of 37
- Computer Vision and Pattern Recognition 137
- Artificial Intelligence 185
- Radiology, Nuclear Medicine and Imaging 20
- Media Technology 7
- Computational Mechanics 8
Countries citing papers authored by Arthur Douillard
This map shows the geographic impact of Arthur Douillard'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 Arthur Douillard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arthur Douillard more than expected).
Fields of papers citing papers by Arthur Douillard
This network shows the impact of papers produced by Arthur Douillard. 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 Arthur Douillard. The network helps show where Arthur Douillard may publish in the future.
Co-authors
The 9 scholars most cited alongside Arthur Douillard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion Hit paper breakdown → | 2022 | 181 |
| 2 | 2022 | 14 | |
| 3 | 2023 | 10 | |
| 4 | 2021 | 4 | |
| 5 | Small-Task Incremental Learning. | 2020 | 2 |
| 6 | 2022 | 2 | |
| 7 | 2021 | 1 |
About Arthur Douillard
Arthur Douillard is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Social Psychology, Atomic and Molecular Physics, and Optics and Radiology, Nuclear Medicine and Imaging, having authored 7 papers that have together received 214 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (5 papers), Advanced Neural Network Applications (4 papers), COVID-19 diagnosis using AI (1 paper), Image Enhancement Techniques (1 paper), Color perception and design (1 paper), Color Science and Applications (1 paper) and Education and Critical Thinking Development (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (137 citations), Artificial Intelligence (185 citations), Radiology, Nuclear Medicine and Imaging (20 citations), Media Technology (7 citations) and Computational Mechanics (8 citations). Arthur Douillard has collaborated with scholars based in France, Brazil and Italy. Frequent co-authors include Matthieu Cord, Alexandre Ramé, Guillaume Couairon, Tuan-Hung Vu, Fabio Cermelli, Patrick Pérez, Arnaud Dapogny, Thomas Robert and Eduardo Valle. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) and arXiv (Cornell University).
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.