Clément Chatelain

1.5k total citations
36 papers, 589 citations indexed

About

Clément Chatelain is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cell Biology. According to data from OpenAlex, Clément Chatelain has authored 36 papers receiving a total of 589 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 17 papers in Artificial Intelligence and 5 papers in Cell Biology. Recurrent topics in Clément Chatelain's work include Handwritten Text Recognition Techniques (15 papers), Natural Language Processing Techniques (6 papers) and Cellular Mechanics and Interactions (5 papers). Clément Chatelain is often cited by papers focused on Handwritten Text Recognition Techniques (15 papers), Natural Language Processing Techniques (6 papers) and Cellular Mechanics and Interactions (5 papers). Clément Chatelain collaborates with scholars based in France, Israel and Canada. Clément Chatelain's co-authors include Thierry Paquet, Martine Ben Amar, Sébastien Adam, Pasquale Ciarletta, Christopher Kermorvant, Romain Hérault, Romain Modzelewski, Laurent Heutte, Mehran Kardar and Yacov Kantor and has published in prestigious journals such as Physical Review Letters, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Clément Chatelain

36 papers receiving 566 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Clément Chatelain France 15 217 144 95 75 75 36 589
Li Xiao China 16 269 1.2× 333 2.3× 118 1.2× 7 0.1× 37 0.5× 61 1.1k
Lisheng Wei China 12 171 0.8× 215 1.5× 43 0.5× 15 0.2× 4 0.1× 54 604
Nicholas S. Flann United States 16 124 0.6× 212 1.5× 133 1.4× 38 0.5× 38 0.5× 57 743
Lia Morra Italy 15 159 0.7× 282 2.0× 75 0.8× 8 0.1× 17 0.2× 49 749
Hieu Trung Huynh Vietnam 14 118 0.5× 269 1.9× 84 0.9× 4 0.1× 7 0.1× 71 652
Eric Christiansen United States 8 218 1.0× 276 1.9× 117 1.2× 17 0.2× 2 0.0× 11 910
Shouvik Chakraborty India 14 331 1.5× 210 1.5× 21 0.2× 5 0.1× 7 0.1× 45 551
Abderrahmane Habbal France 10 35 0.2× 20 0.1× 45 0.5× 36 0.5× 29 0.4× 50 301
Mutlu Mete United States 14 99 0.5× 237 1.6× 65 0.7× 38 0.5× 4 0.1× 51 654
Jiawei Li China 14 145 0.7× 325 2.3× 138 1.5× 9 0.1× 2 0.0× 51 775

Countries citing papers authored by Clément Chatelain

Since Specialization
Citations

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

Fields of papers citing papers by Clément Chatelain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Clément Chatelain

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

All Works

20 of 20 papers shown
1.
Bernard, Simon, et al.. (2023). Domain Translation via Latent Space Mapping. SPIRE - Sciences Po Institutional REpository. 20. 1–10. 1 indexed citations
2.
Chatelain, Clément, et al.. (2023). DAN: A Segmentation-Free Document Attention Network for Handwritten Document Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(7). 8227–8243. 26 indexed citations
3.
Chatelain, Clément, et al.. (2020). Novel methods for epistasis detection in genome-wide association studies. PLoS ONE. 15(11). e0242927–e0242927. 9 indexed citations
4.
Chatelain, Clément, et al.. (2020). Multi-scale Gated Fully Convolutional DenseNets for semantic labeling of historical newspaper images. Pattern Recognition Letters. 131. 435–441. 9 indexed citations
5.
Amyar, Amine, Su Ruan, Isabelle Gardin, et al.. (2019). 3-D RPET-NET: Development of a 3-D PET Imaging Convolutional Neural Network for Radiomics Analysis and Outcome Prediction. IEEE Transactions on Radiation and Plasma Medical Sciences. 3(2). 225–231. 27 indexed citations
6.
Rogozan, Alexandrina, et al.. (2019). Multi-Task Deep Learning for Pedestrian Detection, Action Recognition and Time to Cross Prediction. IEEE Access. 7. 149318–149327. 33 indexed citations
7.
Belharbi, Soufiane, Romain Hérault, Clément Chatelain, & Sébastien Adam. (2017). Deep neural networks regularization for structured output prediction. Neurocomputing. 281. 169–177. 8 indexed citations
8.
Belharbi, Soufiane, Clément Chatelain, Romain Hérault, et al.. (2017). Spotting L3 slice in CT scans using deep convolutional network and transfer learning. Computers in Biology and Medicine. 87. 95–103. 39 indexed citations
9.
Chatelain, Clément, et al.. (2016). Cohort of LSTM and lexicon verification for handwriting recognition with gigantic lexicon.. arXiv (Cornell University). 2 indexed citations
10.
Hebert, David G., et al.. (2016). Language Identification in Document Images. Electronic Imaging. 28(17). 1–16. 3 indexed citations
11.
Chatelain, Clément, et al.. (2015). A Hybrid BLSTM-HMM for Spotting Regular Expressions.. 5–12. 1 indexed citations
12.
Hérault, Romain, et al.. (2015). IODA: An input/output deep architecture for image labeling. Pattern Recognition. 48(9). 2847–2858. 25 indexed citations
13.
Bernard, Simon, Clément Chatelain, Sébastien Adam, & Robert Sabourin. (2015). The Multiclass ROC Front method for cost-sensitive classification. Pattern Recognition. 52. 46–60. 20 indexed citations
14.
Chatelain, Clément, et al.. (2015). Exploring multiple feature combination strategies with a recurrent neural network architecture for off-line handwriting recognition. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9402. 94020F–94020F. 3 indexed citations
15.
Chatelain, Clément, et al.. (2014). Patterns in melanocytic lesions: impact of the geometry on growth and transport inside the epidermis. Journal of The Royal Society Interface. 11(97). 20140339–20140339. 9 indexed citations
16.
Chatelain, Clément, Pasquale Ciarletta, & Martine Ben Amar. (2011). Morphological changes in early melanoma development: Influence of nutrients, growth inhibitors and cell-adhesion mechanisms. Journal of Theoretical Biology. 290. 46–59. 24 indexed citations
17.
Amar, Martine Ben, Clément Chatelain, & Pasquale Ciarletta. (2011). Contour Instabilities in Early Tumor Growth Models. Physical Review Letters. 106(14). 148101–148101. 49 indexed citations
18.
Paquet, Thierry, et al.. (2011). A categorization system for handwritten documents. International Journal on Document Analysis and Recognition (IJDAR). 15(4). 315–330. 7 indexed citations
19.
Chatelain, Clément, et al.. (2010). NONCOST SENSITIVE SVM TRAINING USING MULTIPLE MODEL SELECTION. Journal of Circuits Systems and Computers. 19(1). 231–242. 2 indexed citations
20.
Chatelain, Clément, Yacov Kantor, & Mehran Kardar. (2008). Probability distributions for polymer translocation. Physical Review E. 78(2). 21129–21129. 33 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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