GREYC

38.1k citations
2.2k papers ·

Impact in

Papers in

GREYC

2.0k papers receiving 35.9k citations

Peers

GREYC
Comparison fields: 5 of 228
  • Computer Vision and Pattern Recognition 10.3k
  • Artificial Intelligence 9.4k
  • Control and Systems Engineering 6.1k
  • Signal Processing 2.6k
  • Computational Theory and Mathematics 3.8k
Replace Centre Inria de l'Université de Rennes with:
Centre Inria de l'Université de Rennes France
Institut National des Sciences Appliquées de Rennes France
Laboratoire d'Informatique Gaspard-Monge France
Centre de Recherche en Informatique France
Centre de Recherche en Mathématiques de la Décision France
Laboratoire d'Intégration des Systèmes et des Technologies France
LIP6 France
Département d'Informatique France
Institut Mines-Télécom France
Thales (France) France
GREYC relative to Centre Inria de l'Université de Rennes France Centre Inria de l'Université de Rennes's profile →
Citations per field
00.5×1.5×
Centre Inria de l'Université de Rennes · 1×
Citations per year

Countries citing scholars working at GREYC

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at GREYC. 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 papers produced at GREYC with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites GREYC more than expected).

Fields of papers published by authors at GREYC

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with GREYC at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with GREYC at the time of their publication.

About GREYC

In recent decades, authors affiliated with GREYC have published 2.2k papers, which have received a total of 38.1k indexed citations . Scholars at this organization have produced 521 papers in Computer Vision and Pattern Recognition, 310 papers in Computational Theory and Mathematics, 201 papers in Signal Processing, 548 papers in Artificial Intelligence and 54 papers in Computer Graphics and Computer-Aided Design on the topics of Medical Image Segmentation Techniques (140 papers), Adaptive Control of Nonlinear Systems (97 papers), Image and Signal Denoising Methods (96 papers), Image Retrieval and Classification Techniques (90 papers), Advanced Image and Video Retrieval Techniques (81 papers), Data Mining Algorithms and Applications (76 papers), Control Systems and Identification (73 papers) and Data Management and Algorithms (72 papers). Their work is cited by papers focused on Computer Vision and Pattern Recognition (10.3k citations), Artificial Intelligence (9.4k citations), Control and Systems Engineering (6.1k citations), Signal Processing (2.6k citations) and Computational Theory and Mathematics (3.8k citations). Authors at GREYC collaborate with scholars in France, United States and Morocco and have published in prestigious journals including Lecture notes in computer science, Theoretical Computer Science, Solid-State Electronics, Pattern Recognition Letters and Journal of Applied Physics. Some of GREYC's most productive authors include Jalal Fadili, Claude Carlet, F. Giri, Jean‐Luc Starck, Laurent Condat, David Tschumperlé, Frédéric Jurie, Alain Bretto, Olivier Lézoray and M. Farza.

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.

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