Nicole Vincent

218 total papers · 2.5k total citations
94 papers, 1.2k citations indexed

About

Nicole Vincent is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Nicole Vincent has authored 94 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Computer Vision and Pattern Recognition, 17 papers in Artificial Intelligence and 16 papers in Signal Processing. Recurrent topics in Nicole Vincent's work include Handwritten Text Recognition Techniques (31 papers), Image Retrieval and Classification Techniques (24 papers) and Advanced Image and Video Retrieval Techniques (18 papers). Nicole Vincent is often cited by papers focused on Handwritten Text Recognition Techniques (31 papers), Image Retrieval and Classification Techniques (24 papers) and Advanced Image and Video Retrieval Techniques (18 papers). Nicole Vincent collaborates with scholars based in France, Pakistan and Canada. Nicole Vincent's co-authors include Imran Siddiqi, Claudie Faure, Khurram Khurshid, Sébastien Lefèvre, Florence Cloppet, Momina Moetesum, Imran Siddiqi, Philippe Arbeille, Jean-Yves Ramel and Kathryn Zuj and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Pattern Recognition.

In The Last Decade

Nicole Vincent

87 papers receiving 1.1k citations

Author Peers

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

Author Last Decade Papers Cites
Nicole Vincent 904 280 246 130 102 94 1.2k
Chao Xie 398 0.4× 254 0.9× 151 0.6× 46 0.4× 148 1.5× 86 1.3k
Mounîm A. El‐Yacoubi 539 0.6× 333 1.2× 122 0.5× 393 3.0× 26 0.3× 87 1.3k
Claudio De Stefano 474 0.5× 600 2.1× 98 0.4× 59 0.5× 38 0.4× 90 1.1k
Zhiquan He 487 0.5× 165 0.6× 83 0.3× 82 0.6× 30 0.3× 66 1.1k
Sokratis Makrogiannis 768 0.8× 123 0.4× 125 0.5× 79 0.6× 135 1.3× 70 1.4k
Ruwei Dai 393 0.4× 229 0.8× 89 0.4× 102 0.8× 62 0.6× 75 1.1k
Sumantra Dutta Roy 488 0.5× 121 0.4× 63 0.3× 254 2.0× 181 1.8× 93 1.2k
Kimiaki Shirahama 668 0.7× 302 1.1× 164 0.7× 96 0.7× 21 0.2× 67 1.1k
Bin Kang 722 0.8× 349 1.2× 69 0.3× 45 0.3× 22 0.2× 82 1.2k
Neucimar J. Leite 730 0.8× 112 0.4× 108 0.4× 197 1.5× 24 0.2× 51 1.5k

Countries citing papers authored by Nicole Vincent

Since Specialization
Citations

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

Fields of papers citing papers by Nicole Vincent

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicole Vincent

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