Claude Cariou

672 total citations
37 papers, 411 citations indexed

About

Claude Cariou is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Claude Cariou has authored 37 papers receiving a total of 411 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Vision and Pattern Recognition, 21 papers in Media Technology and 9 papers in Artificial Intelligence. Recurrent topics in Claude Cariou's work include Remote-Sensing Image Classification (21 papers), Image Retrieval and Classification Techniques (15 papers) and Medical Image Segmentation Techniques (7 papers). Claude Cariou is often cited by papers focused on Remote-Sensing Image Classification (21 papers), Image Retrieval and Classification Techniques (15 papers) and Medical Image Segmentation Techniques (7 papers). Claude Cariou collaborates with scholars based in France, New Zealand and Norway. Claude Cariou's co-authors include Kacem Chehdi, Steven Le Moan, Jonathan Cheung-Wai Chan, Luca Demarchi, Frank Canters, Giorgio Licciardi, Jean-Marc Ogier, Rémy Mullot, Olivier Alata and Mohamed Najim and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Access and Remote Sensing.

In The Last Decade

Claude Cariou

32 papers receiving 396 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Claude Cariou France 10 235 169 104 62 54 37 411
Javier Resano Spain 15 289 1.2× 152 0.9× 187 1.8× 75 1.2× 49 0.9× 42 721
Aiye Shi China 11 180 0.8× 179 1.1× 112 1.1× 58 0.9× 42 0.8× 55 455
Boao Qin China 8 314 1.3× 161 1.0× 148 1.4× 88 1.4× 34 0.6× 15 499
Xuanwen Tao Spain 13 308 1.3× 153 0.9× 144 1.4× 73 1.2× 37 0.7× 31 474
Yuxi Sun China 10 289 1.2× 234 1.4× 168 1.6× 91 1.5× 42 0.8× 25 606
Michał Myller Poland 10 260 1.1× 137 0.8× 112 1.1× 94 1.5× 73 1.4× 16 427
Taylor Glenn United States 6 181 0.8× 73 0.4× 97 0.9× 75 1.2× 50 0.9× 15 305
Wenhua Zhang China 14 250 1.1× 294 1.7× 97 0.9× 79 1.3× 40 0.7× 47 572
Alp Ertürk Türkiye 11 381 1.6× 200 1.2× 214 2.1× 41 0.7× 73 1.4× 61 555
Xianchuan Yu China 12 499 2.1× 207 1.2× 282 2.7× 101 1.6× 59 1.1× 55 672

Countries citing papers authored by Claude Cariou

Since Specialization
Citations

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

Fields of papers citing papers by Claude Cariou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Claude Cariou

This figure shows the co-authorship network connecting the top 25 collaborators of Claude Cariou. A scholar is included among the top collaborators of Claude Cariou 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 Claude Cariou. Claude Cariou 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.
Wang, Yuding, Kacem Chehdi, Claude Cariou, & Benoît Vozel. (2023). Data Stream Unsupervised Partitioning Based on Optimized Fuzzy C-Means. SPIRE - Sciences Po Institutional REpository. 7265–7268. 1 indexed citations
2.
Cariou, Claude, Steven Le Moan, & Kacem Chehdi. (2022). A Novel Mean-Shift Algorithm for Data Clustering. IEEE Access. 10. 14575–14585. 31 indexed citations
3.
Chehdi, Kacem, et al.. (2022). Unsupervised and Automatic Training Samples Selection Method. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. 271–274.
4.
Chehdi, Kacem, et al.. (2021). Hierarchical Unsupervised Partitioning of Large Size Data and Its Application to Hyperspectral Images. Remote Sensing. 13(23). 4874–4874. 4 indexed citations
5.
Moan, Steven Le & Claude Cariou. (2020). Minimax Bridgeness-Based Clustering for Hyperspectral Data. Remote Sensing. 12(7). 1162–1162. 8 indexed citations
6.
Cariou, Claude, Steven Le Moan, & Kacem Chehdi. (2020). Improving K-Nearest Neighbor Approaches for Density-Based Pixel Clustering in Hyperspectral Remote Sensing Images. Remote Sensing. 12(22). 3745–3745. 18 indexed citations
7.
Chehdi, Kacem & Claude Cariou. (2019). Learning or assessment of classification algorithms relying on biased ground truth data: what interest?. Journal of Applied Remote Sensing. 13(3). 1–1. 9 indexed citations
8.
Chen, Bingqiu, et al.. (2016). Unsupervised component reduction of hyperspectral images and clustering without performance loss: application to marine algae identification. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10004. 100040Q–100040Q. 2 indexed citations
9.
Cariou, Claude & Kacem Chehdi. (2015). Unsupervised Nearest Neighbors Clustering With Application to Hyperspectral Images. IEEE Journal of Selected Topics in Signal Processing. 9(6). 1105–1116. 51 indexed citations
10.
Chehdi, Kacem, et al.. (2015). Stable and unsupervised fuzzy C-means method and its validation in the context of multicomponent images. Journal of Electronic Imaging. 24(6). 61117–61117. 4 indexed citations
11.
Chehdi, Kacem, et al.. (2015). Unsupervised and stable LBG algorithm for data classification: application to aerial multicomponent images. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9643. 96431I–96431I. 1 indexed citations
12.
Chen, Bingqiu, et al.. (2015). Unsupervised hierarchical partitioning of hyperspectral images: application to marine algae identification. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2 indexed citations
13.
Demarchi, Luca, Frank Canters, Claude Cariou, Giorgio Licciardi, & Jonathan Cheung-Wai Chan. (2013). Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping. ISPRS Journal of Photogrammetry and Remote Sensing. 87. 166–179. 55 indexed citations
14.
Cariou, Claude & Kacem Chehdi. (2006). Semi-Rigid Registration of Remote Sensing Airborne Scanner Images. 2. II–825. 1 indexed citations
15.
Cariou, Claude, et al.. (2005). Spectral Analysis Of Ocean Wave Imagery Using 2-d Linear Prediction. 1. 127–130.
16.
17.
Ogier, Jean-Marc, et al.. (2000). Symbol and character recognition: application to engineering drawings. International Journal on Document Analysis and Recognition (IJDAR). 3(2). 89–101. 49 indexed citations
18.
Adam, Sébastien, et al.. (1999). Multi-scaled and multi oriented character recognition: an original strategy. 45–48. 2 indexed citations
19.
Cariou, Claude & Kacem Chehdi. (1996). Unsupervised Texture Segmentation Using 2-D Ar Modeling And A Stochastic Version Of The Em Procedure. INFM-OAR (INFN Catania). 1–4. 1 indexed citations
20.
Larouche, Pierre & Claude Cariou. (1992). Directional Wave Spectra Estimation in a Marginal Ice Zone Using Linear Prediction. Journal of Physical Oceanography. 22(2). 196–206. 3 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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