Florence Cloppet

56 total papers · 536 total citations
22 papers, 249 citations indexed

About

Florence Cloppet is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biophysics. According to data from OpenAlex, Florence Cloppet has authored 22 papers receiving a total of 249 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 6 papers in Biophysics. Recurrent topics in Florence Cloppet's work include Image Retrieval and Classification Techniques (9 papers), Cell Image Analysis Techniques (5 papers) and Medical Image Segmentation Techniques (5 papers). Florence Cloppet is often cited by papers focused on Image Retrieval and Classification Techniques (9 papers), Cell Image Analysis Techniques (5 papers) and Medical Image Segmentation Techniques (5 papers). Florence Cloppet collaborates with scholars based in France, Pakistan and Tunisia. Florence Cloppet's co-authors include Nicole Vincent, Imran Siddiqi, Momina Moetesum, Georges Stamon, Oriol Ramos Terrades, Salvatore Tabbone, Laure Fournier, Dorra Sellami, Laurent Wendling and Georges Semaan and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Pattern Recognition.

In The Last Decade

Florence Cloppet

19 papers receiving 238 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Florence Cloppet 133 74 58 49 38 22 249
Akmal A. Younis 124 0.9× 44 0.6× 101 1.7× 13 0.3× 13 0.3× 20 329
Juan E. Arco 79 0.6× 70 0.9× 14 0.2× 18 0.4× 15 0.4× 22 322
Boris Mansencal 69 0.5× 44 0.6× 18 0.3× 5 0.1× 35 0.9× 20 253
Ebrahim Mohammed Senan 67 0.5× 139 1.9× 19 0.3× 7 0.1× 20 0.5× 18 324
Jianping Qiao 63 0.5× 33 0.4× 24 0.4× 7 0.1× 8 0.2× 29 315
Samadrita Roy Chowdhury 93 0.7× 37 0.5× 6 0.1× 11 0.2× 23 0.6× 13 262
Andrea Rueda 137 1.0× 19 0.3× 19 0.3× 5 0.1× 27 0.7× 22 273
Jiayue Cai 40 0.3× 104 1.4× 43 0.7× 11 0.2× 7 0.2× 20 286
Chang Liu 71 0.5× 20 0.3× 18 0.3× 4 0.1× 10 0.3× 32 252
Shiwei Ye 25 0.2× 66 0.9× 7 0.1× 23 0.5× 17 0.4× 41 296

Countries citing papers authored by Florence Cloppet

Since Specialization
Citations

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

Fields of papers citing papers by Florence Cloppet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Florence Cloppet

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

All Works

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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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