Matthieu Cord
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Signal Processing
- Media Technology
- Biomedical Engineering
- Co-authors
- Philippe H. GosselinSylvie Philipp‐FoliguetFŕed́eric PreciosoMatthijs DouzeJenny Benois‐PineauJ.-Y. HerveEduardo Valle
- Topics
- Image Retrieval and Classification Techniques (5 papers)Advanced Image and Video Retrieval Techniques (3 papers)Video Analysis and Summarization (2 papers)
- Journals
- IEEE Transactions on Image ProcessingJournal of Electronic ImagingSpringerBriefs in computer science
- Partner nations
- FranceUnited States
In The Last Decade
Matthieu Cord
9 papers receiving 225 citations
Peers
Comparison fields: 5 of 95
- Computer Vision and Pattern Recognition 105
- Artificial Intelligence 73
- Signal Processing 22
- Media Technology 19
- Biomedical Engineering 16
Countries citing papers authored by Matthieu Cord
This map shows the geographic impact of Matthieu Cord'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 Matthieu Cord with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthieu Cord more than expected).
Fields of papers citing papers by Matthieu Cord
This network shows the impact of papers produced by Matthieu Cord. 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 Matthieu Cord. The network helps show where Matthieu Cord may publish in the future.
Co-authorship network of co-authors of Matthieu Cord
This figure shows the co-authorship network connecting the top 25 collaborators of Matthieu Cord. A scholar is included among the top collaborators of Matthieu Cord based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthieu Cord. Matthieu Cord is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Training data-efficient image transformers & distillation through attention | 6 |
| 2 | 2 | |
| 3 | Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval (Cognitive Technologies) | 6 |
| 4 | 66 | |
| 5 | 5 | |
| 6 | 96 | |
| 7 | 46 | |
| 8 | 1 | |
| 9 | 6 |
About Matthieu Cord
Matthieu Cord is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 9 papers that have together received 234 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (5 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Video Analysis and Summarization (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (105 citations), Health Informatics (4 citations) and Artificial Intelligence (73 citations). Matthieu Cord has collaborated with scholars based in France and United States. Frequent co-authors include Philippe H. Gosselin, Sylvie Philipp‐Foliguet, Fŕed́eric Precioso, Matthijs Douze, Jenny Benois‐Pineau, J.-Y. Herve and Eduardo Valle. Their work appears in journals such as IEEE Transactions on Image Processing, Journal of Electronic Imaging and SpringerBriefs 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.