Pierre-Alain Moëllic
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Molecular Biology
- Signal Processing
- Computer Networks and Communications
- Co-authors
- Christophe MilletAdrian PopescuJean-Max DutertreIsabelle BlochGregory GrefenstetteHervé Le BorgneOlivier FerretNasredine Semmar
- Topics
- Image Retrieval and Classification Techniques (12 papers)Advanced Image and Video Retrieval Techniques (11 papers)Adversarial Robustness in Machine Learning (3 papers)
- Journals
- Image and Vision ComputingAnnals of TelecommunicationsHAL (Le Centre pour la Communication Scientifique Directe)
- Partner nations
- FranceUnited States
In The Last Decade
Pierre-Alain Moëllic
15 papers receiving 88 citations
Peers
Comparison fields: 5 of 22
- Computer Vision and Pattern Recognition 80
- Artificial Intelligence 36
- Molecular Biology 16
- Signal Processing 10
- Computer Networks and Communications 5
Countries citing papers authored by Pierre-Alain Moëllic
This map shows the geographic impact of Pierre-Alain Moëllic'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 Pierre-Alain Moëllic with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pierre-Alain Moëllic more than expected).
Fields of papers citing papers by Pierre-Alain Moëllic
This network shows the impact of papers produced by Pierre-Alain Moëllic. 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 Pierre-Alain Moëllic. The network helps show where Pierre-Alain Moëllic may publish in the future.
Co-authorship network of co-authors of Pierre-Alain Moëllic
This figure shows the co-authorship network connecting the top 25 collaborators of Pierre-Alain Moëllic. A scholar is included among the top collaborators of Pierre-Alain Moëllic 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 Pierre-Alain Moëllic. Pierre-Alain Moëllic is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 0 | |
| 3 | 8 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | Visual Reranking for Image Retrieval over the Wikipedia Corpus. | 2 |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 17 | |
| 10 | 8 | |
| 11 | 5 | |
| 12 | 9 | |
| 13 | 2 | |
| 14 | 9 | |
| 15 | 8 | |
| 16 | 15 |
About Pierre-Alain Moëllic
Pierre-Alain Moëllic is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Media Technology, having authored 16 papers that have together received 97 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (12 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Adversarial Robustness in Machine Learning (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (80 citations), Artificial Intelligence (36 citations) and Signal Processing (10 citations). Pierre-Alain Moëllic has collaborated with scholars based in France and United States. Frequent co-authors include Christophe Millet, Adrian Popescu, Jean-Max Dutertre, Isabelle Bloch, Gregory Grefenstette, Hervé Le Borgne, Olivier Ferret, Nasredine Semmar, Svitlana Zinger and Romaric Besançon. Their work appears in journals such as Image and Vision Computing, Annals of Telecommunications and HAL (Le Centre pour la Communication Scientifique Directe).
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.