Catherine Garbay

1.2k total citations
50 papers, 691 citations indexed

About

Catherine Garbay is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Catherine Garbay has authored 50 papers receiving a total of 691 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Vision and Pattern Recognition, 17 papers in Artificial Intelligence and 6 papers in Signal Processing. Recurrent topics in Catherine Garbay's work include Medical Image Segmentation Techniques (17 papers), Multi-Agent Systems and Negotiation (6 papers) and Cell Image Analysis Techniques (6 papers). Catherine Garbay is often cited by papers focused on Medical Image Segmentation Techniques (17 papers), Multi-Agent Systems and Negotiation (6 papers) and Cell Image Analysis Techniques (6 papers). Catherine Garbay collaborates with scholars based in France, Brazil and Italy. Catherine Garbay's co-authors include Michel Dojat, Benoît Scherrer, Florence Forbes, J.-M. Chassery, G Brugal, Nathalie Richard, Vincent Rialle, Alain Boucher, Thomas Guyet and Chris Taylor and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.

In The Last Decade

Catherine Garbay

46 papers receiving 631 citations

Peers

Catherine Garbay

CVPR

NEURO

RNMI

BIOPH

Maria Frucci Italy

Changhee Han Japan

Feng Yan China

Omar S. Al-Kadi Jordan

Siew Chin Neoh Malaysia

Margarita Gamarra Colombia

Wanli Liu China

Piotr Mardziel United States

Hiroharu Kawanaka Japan

Maria Frucci Italy

Catherine Garbay

272 ×0.7

CVPR

193 ×0.9

32 ×0.3

NEURO

159 ×1.7

RNMI

52 ×0.7

BIOPH

Citations per year, relative to Catherine Garbay Catherine Garbay (= 1×) peers Maria Frucci

Countries citing papers authored by Catherine Garbay

Since Specialization

Citations

This map shows the geographic impact of Catherine Garbay'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 Catherine Garbay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Catherine Garbay more than expected).

Fields of papers citing papers by Catherine Garbay

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Catherine Garbay. 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 Catherine Garbay. The network helps show where Catherine Garbay may publish in the future.

Co-authorship network of co-authors of Catherine Garbay

This figure shows the co-authorship network connecting the top 25 collaborators of Catherine Garbay. A scholar is included among the top collaborators of Catherine Garbay 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 Catherine Garbay. Catherine Garbay is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Garbay, Catherine, et al.. (2014). Abductive Agents for Human Activity Monitoring. International Journal of Artificial Intelligence Tools. 23(1). 1440002–1440002. 11 indexed citations

Scherrer, Benoît, Florence Forbes, Catherine Garbay, & Michel Dojat. (2009). Distributed Local MRF Models for Tissue and Structure Brain Segmentation. IEEE Transactions on Medical Imaging. 28(8). 1278–1295. 52 indexed citations

Scherrer, Benoît, Florence Forbes, Catherine Garbay, & Michel Dojat. (2008). Fully Bayesian Joint Model for MR Brain Scan Tissue and Structure Segmentation. Lecture notes in computer science. 11(Pt 2). 1066–1074. 13 indexed citations

Scherrer, Benoît, Michel Dojat, Florence Forbes, & Catherine Garbay. (2008). Agentification of Markov model-based segmentation: Application to magnetic resonance brain scans. Artificial Intelligence in Medicine. 46(1). 81–95. 10 indexed citations

Jaillard, Assia, et al.. (2007). Segmentation of Magnetic Resonance Brain Images Using Edge and Region Cooperation Characterization of Stroke Lesions.. The International Arab Journal of Information Technology. 4. 281–288. 5 indexed citations

Guyet, Thomas, Catherine Garbay, & Michel Dojat. (2007). Knowledge construction from time series data using a collaborative exploration system. Journal of Biomedical Informatics. 40(6). 672–687. 28 indexed citations

Scherrer, Benoît, Michel Dojat, Florence Forbes, & Catherine Garbay. (2007). LOCUS: LOcal Cooperative Unified Segmentation of MRI Brain Scans. Lecture notes in computer science. 10(Pt 1). 219–227. 8 indexed citations

Richard, Nathalie, Michel Dojat, & Catherine Garbay. (2007). Distributed Markovian segmentation: Application to MR brain scans. Pattern Recognition. 40(12). 3467–3480. 22 indexed citations

Garbay, Catherine, et al.. (2006). Learning recurrent behaviors from heterogeneous multivariate time-series. Artificial Intelligence in Medicine. 39(1). 25–47. 30 indexed citations

10.

Richard, Nathalie, Michel Dojat, & Catherine Garbay. (2004). Automated segmentation of human brain MR images using a multi-agent approach. Artificial Intelligence in Medicine. 30(2). 153–176. 34 indexed citations

11.

Richard, Nathalie, Michel Dojat, & Catherine Garbay. (2002). Situated cooperative agents: a powerful paradigm for MRI brain scans segmentation. European Conference on Artificial Intelligence. 33–37. 1 indexed citations

12.

Labarre‐Vila, Annick, et al.. (2002). A knowledge-driven agent-centred framework for data mining in EMG. Comptes Rendus Biologies. 325(4). 375–382. 8 indexed citations

13.

Dojat, Michel, et al.. (2000). A cooperative framework for segmentation of MRI brain scans. Artificial Intelligence in Medicine. 20(1). 77–93. 35 indexed citations

14.

Garbay, Catherine, et al.. (1998). A Mechanical Model to Simulate Cell Reorganisation during In-Vitro Wound Healing. 343–347. 2 indexed citations

15.

Boucher, Alain, et al.. (1998). A society of goal-oriented agents for the analysis of living cells. Artificial Intelligence in Medicine. 14(1-2). 183–199. 16 indexed citations

16.

Boucher, Alain, et al.. (1998). Cell Migration Analysis After In Vitro Wounding Injury with a Multi-Agent Approach. Artificial Intelligence Review. 12(1-3). 137–162. 10 indexed citations

17.

Keravnou, Elpida, Catherine Garbay, Robert Baud, & Jeremy C Wyatt. (1997). Proceedings of the 6th Conference on Artificial Intelligence in Medicine in Europe. 6 indexed citations

18.

Garbay, Catherine, et al.. (1996). A multi-agent approach to edge detection as a distributed optimization problem. 2. 81–85 vol.2. 6 indexed citations

19.

Garbay, Catherine. (1986). Image Structure Representation and Processing: A Discussion of Some Segmentation Methods in Cytology. IEEE Transactions on Pattern Analysis and Machine Intelligence. PAMI-8(2). 140–146. 59 indexed citations

20.

Chassery, J.-M. & Catherine Garbay. (1984). An Iterative Segmentation Method Based on a Contextual Color and Shape Criterion. IEEE Transactions on Pattern Analysis and Machine Intelligence. PAMI-6(6). 794–800. 60 indexed citations

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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