Yves Lechevallier

1.6k total citations
43 papers, 736 citations indexed

About

Yves Lechevallier is a scholar working on Artificial Intelligence, Signal Processing and Information Systems. According to data from OpenAlex, Yves Lechevallier has authored 43 papers receiving a total of 736 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 20 papers in Signal Processing and 10 papers in Information Systems. Recurrent topics in Yves Lechevallier's work include Data Management and Algorithms (17 papers), Advanced Clustering Algorithms Research (16 papers) and Neural Networks and Applications (8 papers). Yves Lechevallier is often cited by papers focused on Data Management and Algorithms (17 papers), Advanced Clustering Algorithms Research (16 papers) and Neural Networks and Applications (8 papers). Yves Lechevallier collaborates with scholars based in France, Brazil and Canada. Yves Lechevallier's co-authors include Francisco de A.T. de Carvalho, Marie Chavent, Edwin Diday, Renata M.C.R. de Souza, Bernard Burtschy, Patrice Bertrand, Rosanna Verde, Olivier Briant, Fabrice Rossi and Georges Hébrail and has published in prestigious journals such as Pattern Recognition, Information Sciences and Fuzzy Sets and Systems.

In The Last Decade

Yves Lechevallier

38 papers receiving 694 citations

Peers

Yves Lechevallier

CTM

CVPR

Hans‐Hermann Bock Germany

Renata M.C.R. de Souza Brazil

Paula Brito Portugal

Arno Siebes Netherlands

Christian Posse United States

Rosanna Verde Italy

Georg Peters Germany

Claudio Moraga Germany

Alfonso Gordaliza Spain

Rosa Meo Italy

Hans‐Hermann Bock Germany

Yves Lechevallier

406 ×0.9

148 ×0.9

117 ×0.7

CTM

136 ×1.1

CVPR

88 ×0.8

Citations per year, relative to Yves Lechevallier Yves Lechevallier (= 1×) peers Hans‐Hermann Bock

Countries citing papers authored by Yves Lechevallier

Since Specialization

Citations

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

Fields of papers citing papers by Yves Lechevallier

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yves Lechevallier

This figure shows the co-authorship network connecting the top 25 collaborators of Yves Lechevallier. A scholar is included among the top collaborators of Yves Lechevallier 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 Yves Lechevallier. Yves Lechevallier 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

Carvalho, Francisco de A.T. de, et al.. (2013). A Fuzzy C-Medoids Clustering Algorithm Based on Multiple Dissimilarity Matrices. 107–112. 2 indexed citations

Carvalho, Francisco de A.T. de, et al.. (2011). Partitioning hard clustering algorithms based on multiple dissimilarity matrices. Pattern Recognition. 45(1). 447–464. 46 indexed citations

Hébrail, Georges, et al.. (2009). Simultaneous Clustering and Segmentation for Functional Data.. The European Symposium on Artificial Neural Networks. 4 indexed citations

Carvalho, Francisco de A.T. de & Yves Lechevallier. (2008). Partitional clustering algorithms for symbolic interval data based on single adaptive distances. Pattern Recognition. 42(7). 1223–1236. 59 indexed citations

Ciampi, Antonio, Yves Lechevallier, Manuel Castejón‐Limas, & Ana González‐Marcos. (2007). Hierarchical clustering of subpopulations with a dissimilarity based on the likelihood ratio statistic: application to clustering massive data sets. Pattern Analysis and Applications. 11(2). 199–220. 4 indexed citations

Lechevallier, Yves, et al.. (2007). Analyzing Distance Measures for Symbolic Data Based on Fuzzy Clustering. 109–114. 1 indexed citations

Vercoustre, Anne-Marie, et al.. (2006). Classification de documents XML à partir d'une représentation linéaire des arbres de ces documents.. HAL (Le Centre pour la Communication Scientifique Directe). 2. 433–444. 2 indexed citations

Chavent, Marie, Francisco de A.T. de Carvalho, Yves Lechevallier, & Rosanna Verde. (2006). New clustering methods for interval data. Computational Statistics. 21(2). 211–229. 61 indexed citations

Lechevallier, Yves, et al.. (2005). Pre-Processing and Clustering Complex Data in E-Commerce Domain. HAL (Le Centre pour la Communication Scientifique Directe). 6 indexed citations

10.

Rossi, Fabrice, et al.. (2005). Usage Guided Clustering of Web Pages with the Median Self Organizing Map. The European Symposium on Artificial Neural Networks. 351–356. 5 indexed citations

11.

Carvalho, Francisco de A.T. de, Renata M.C.R. de Souza, Marie Chavent, & Yves Lechevallier. (2005). Adaptive Hausdorff distances and dynamic clustering of symbolic interval data. Pattern Recognition Letters. 27(3). 167–179. 131 indexed citations

12.

Awasthi, Anjali, Yves Lechevallier, Michel Parent, & J.-M. Proth. (2005). Rule based prediction of fastest paths on urban networks. 46. 978–983. 9 indexed citations

13.

Chavent, Marie, et al.. (2003). Trois nouvelles méthodes de classification automatique de données symboliques de type intervalle. French digital mathematics library (Numdam). 51(4). 5–29. 12 indexed citations

14.

Chavent, Marie, Christiane Guinot, Yves Lechevallier, & Michel Tenenhaus. (1999). Méthodes divisives de classification et segmentation non supervisée : recherche d'une typologie de la peau humaine saine. French digital mathematics library (Numdam). 47(4). 87–99. 9 indexed citations

15.

Ciampi, Antonio & Yves Lechevallier. (1997). Statistical models as building blocks of neural networks. Communication in Statistics- Theory and Methods. 26(4). 991–1009. 6 indexed citations

16.

Ciampi, Antonio & Yves Lechevallier. (1995). Designing neural networks from statistical models: a new approach to data exploration. Knowledge Discovery and Data Mining. 45–50. 1 indexed citations

17.

Ciampi, Antonio & Yves Lechevallier. (1995). Reseaux de neurones et modeles statistiques. 15(15). 27–46.

18.

Lechevallier, Yves, et al.. (1994). Short term traffic forecasting by neural networks. 1 indexed citations

19.

Véhel, Jacques Lévy, et al.. (1992). 5 - ARTHUR: un système d'analyse de texture. Traitement du signal. 9(6). 507–517.

20.

Celeux, Gilles & Yves Lechevallier. (1982). Méthodes de segmentation non paramétriques. French digital mathematics library (Numdam). 30(4). 39–53. 2 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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