Alexandre Ramé
Impact in
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- Multimodal Machine Learning Applications
- Generative Adversarial Networks and Image Synthesis
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Face recognition and analysis
- Artificial Intelligence top 10%
- Domain Adaptation and Few-Shot Learning
- Machine Learning and ELM
Papers in
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- Advanced Neural Network Applications 2
- Advanced Image and Video Retrieval Techniques 1
- Image Enhancement Techniques 1
- Generative Adversarial Networks and Image Synthesis 1
- Co-authors
- Matthieu Cord (3 shared papers)Arthur Douillard (2 shared papers)Guillaume Couairon (1 shared paper)Hedi Ben-younes (1 shared paper)Nicolas Thome (1 shared paper)Léonard Hussenot (1 shared paper)Geoffrey Cideron (1 shared paper)Rahul Kidambi (1 shared paper)
- Journals
- arXiv (Cornell University) (1 paper)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)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)
In The Last Decade
Alexandre Ramé
5 papers receiving 347 citations
Alexandre Ramé's Hit Papers
Peers
Comparison fields: 5 of 55
- Computer Vision and Pattern Recognition 231
- Artificial Intelligence 242
- Computational Mechanics 27
- Industrial and Manufacturing Engineering 13
- Media Technology 11
Countries citing papers authored by Alexandre Ramé
This map shows the geographic impact of Alexandre Ramé'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 Alexandre Ramé with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexandre Ramé more than expected).
Fields of papers citing papers by Alexandre Ramé
This network shows the impact of papers produced by Alexandre Ramé. 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 Alexandre Ramé. The network helps show where Alexandre Ramé may publish in the future.
Co-authors
The 18 scholars most cited alongside Alexandre Ramé, 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 | 241 |
| 2 | 2017 | 80 | |
| 3 | 2021 | 27 | |
| 4 | 2022 | 3 | |
| 5 | 2022 | 2 | |
| 6 | 2024 | 0 |
About Alexandre Ramé
Alexandre Ramé is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Social Psychology and Computational Mechanics, having authored 6 papers that have together received 353 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (2 papers), Advanced Neural Network Applications (2 papers), Advanced Image and Video Retrieval Techniques (1 paper), Color Science and Applications (1 paper), Image Enhancement Techniques (1 paper), Adversarial Robustness in Machine Learning (1 paper), Color perception and design (1 paper) and Generative Adversarial Networks and Image Synthesis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (231 citations), Artificial Intelligence (242 citations), Computational Mechanics (27 citations), Industrial and Manufacturing Engineering (13 citations) and Media Technology (11 citations). Alexandre Ramé has collaborated with scholars based in France and Australia. Frequent co-authors include Matthieu Cord, Arthur Douillard, Guillaume Couairon, Hedi Ben-younes, Nicolas Thome, Léonard Hussenot, Geoffrey Cideron, Rahul Kidambi, Hongkun Yu and Aranyak Mehta. Their work appears in journals such as arXiv (Cornell University), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.