Mickaël Coustaty

1.9k total citations
55 papers, 514 citations indexed

About

Mickaël Coustaty is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Mickaël Coustaty has authored 55 papers receiving a total of 514 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Computer Vision and Pattern Recognition, 30 papers in Artificial Intelligence and 5 papers in Information Systems. Recurrent topics in Mickaël Coustaty's work include Handwritten Text Recognition Techniques (20 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Topic Modeling (10 papers). Mickaël Coustaty is often cited by papers focused on Handwritten Text Recognition Techniques (20 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Topic Modeling (10 papers). Mickaël Coustaty collaborates with scholars based in France, Pakistan and United States. Mickaël Coustaty's co-authors include Antoine Doucet, Adam Jatowt, Malik Muhammad Saad Missen, Muhammad Muzzamil Luqman, Zuheng Ming, Marçal Rusiñol, Jean-Marc Ogier, Mujtaba Husnain, Shahzad Mumtaz and Christophe Rigaud and has published in prestigious journals such as IEEE Access, ACM Computing Surveys and Pattern Recognition.

In The Last Decade

Mickaël Coustaty

47 papers receiving 486 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mickaël Coustaty France 12 262 226 59 56 24 55 514
Yuan Tian China 16 229 0.9× 306 1.4× 88 1.5× 30 0.5× 39 1.6× 78 614
Faisal Ahmed Bangladesh 10 367 1.4× 386 1.7× 73 1.2× 13 0.2× 38 1.6× 32 739
Sarath Chandar Canada 9 124 0.5× 374 1.7× 30 0.5× 12 0.2× 13 0.5× 26 511
Jinpeng Wang China 17 457 1.7× 502 2.2× 65 1.1× 13 0.2× 18 0.8× 58 810
Ashraf Y. A. Maghari Palestinian Territory 11 133 0.5× 185 0.8× 80 1.4× 33 0.6× 9 0.4× 35 434
Chaoyang He United States 11 110 0.4× 516 2.3× 107 1.8× 21 0.4× 56 2.3× 22 711
Felix Wu United States 13 396 1.5× 900 4.0× 76 1.3× 26 0.5× 22 0.9× 19 1.1k
Changying Du China 13 211 0.8× 309 1.4× 71 1.2× 30 0.5× 8 0.3× 27 531
Michele Merler United States 14 393 1.5× 197 0.9× 56 0.9× 21 0.4× 24 1.0× 35 597
Hela Ltifi Tunisia 13 144 0.5× 156 0.7× 38 0.6× 14 0.3× 14 0.6× 64 424

Countries citing papers authored by Mickaël Coustaty

Since Specialization
Citations

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

Fields of papers citing papers by Mickaël Coustaty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mickaël Coustaty

This figure shows the co-authorship network connecting the top 25 collaborators of Mickaël Coustaty. A scholar is included among the top collaborators of Mickaël Coustaty 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 Mickaël Coustaty. Mickaël Coustaty 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.
Coustaty, Mickaël, et al.. (2025). Deep metric learning for end-to-end document classification. Neurocomputing. 653. 131241–131241.
2.
Coustaty, Mickaël, et al.. (2024). Built-up areas of nineteenth-century Britain. An integrated methodology for extracting high-resolution urban footprints from historical maps. Historical Methods A Journal of Quantitative and Interdisciplinary History. 57(1). 1–19.
3.
Coustaty, Mickaël, et al.. (2024). Digitizing History: Transitioning Historical Paper Documents to Digital Content for Information Retrieval and Mining—A Comprehensive Survey. IEEE Transactions on Computational Social Systems. 11(5). 6151–6180. 2 indexed citations
4.
Missen, Malik Muhammad Saad, et al.. (2024). A histogram-based approach to calculate graph similarity using graph neural networks. Pattern Recognition Letters. 186. 286–291. 2 indexed citations
5.
Ming, Zuheng, et al.. (2024). Identifying fraudulent identity documents by analyzing imprinted guilloche patterns. Multimedia Tools and Applications. 83(33). 79145–79192.
6.
Ming, Zuheng, et al.. (2023). VLCDoC: Vision-Language contrastive pre-training model for cross-Modal document classification. Pattern Recognition. 139. 109419–109419. 28 indexed citations
7.
Coustaty, Mickaël, et al.. (2023). Automatic classification of company’s document stream: Comparison of two solutions. Pattern Recognition Letters. 172. 181–187. 1 indexed citations
8.
Coustaty, Mickaël, et al.. (2023). An Enhanced Prototypical Network Architecture for Few-Shot Handwritten Urdu Character Recognition. IEEE Access. 11. 33682–33696. 3 indexed citations
9.
Hamdi, Ahmed, Elvys Linhares Pontes, Nicolas Sidère, Mickaël Coustaty, & Antoine Doucet. (2022). In-depth analysis of the impact of OCR errors on named entity recognition and linking. Natural Language Engineering. 29(2). 425–448. 7 indexed citations
10.
Ming, Zuheng, et al.. (2021). EAML: ensemble self-attention-based mutual learning network for document image classification. International Journal on Document Analysis and Recognition (IJDAR). 24(3). 251–268. 7 indexed citations
11.
Caicedo, Juan Carlos, et al.. (2021). Deep multimodal learning for cross-modal retrieval: One model for all tasks. Pattern Recognition Letters. 146. 38–45. 11 indexed citations
12.
Husnain, Mujtaba, Malik Muhammad Saad Missen, Shahzad Mumtaz, et al.. (2021). Urdu Handwritten Characters Data Visualization and Recognition Using Distributed Stochastic Neighborhood Embedding and Deep Network. Complexity. 2021(1).
13.
Husnain, Mujtaba, et al.. (2020). Urdu handwritten text recognition: a survey. IET Image Processing. 14(11). 2291–2300. 14 indexed citations
14.
Missen, Malik Muhammad Saad, et al.. (2020). Additive Angular Margin Loss in Deep Graph Neural Network Classifier for Learning Graph Edit Distance. IEEE Access. 8. 201752–201761. 8 indexed citations
15.
Missen, Malik Muhammad Saad, Mickaël Coustaty, Gyu Sang Choi, et al.. (2020). Correction: OpinionML—Opinion Markup Language for Sentiment Representation. Symmetry 2019, 11, 545. Symmetry. 12(2). 187–187. 1 indexed citations
16.
Missen, Malik Muhammad Saad, Mickaël Coustaty, Gyu Sang Choi, et al.. (2019). OpinionML—Opinion Markup Language for Sentiment Representation. Symmetry. 11(4). 545–545. 6 indexed citations
17.
Husnain, Mujtaba, Malik Muhammad Saad Missen, Shahzad Mumtaz, et al.. (2019). Visualization of High-Dimensional Data by Pairwise Fusion Matrices Using t-SNE. Symmetry. 11(1). 107–107. 25 indexed citations
18.
Husnain, Mujtaba, Malik Muhammad Saad Missen, Shahzad Mumtaz, et al.. (2019). Recognition of Urdu Handwritten Characters Using Convolutional Neural Network. Applied Sciences. 9(13). 2758–2758. 37 indexed citations
19.
Missen, Malik Muhammad Saad, et al.. (2019). Systematic review and usability evaluation of writing mobile apps for children. New Review of Hypermedia and Multimedia. 25(3). 137–160. 12 indexed citations
20.
Missen, Malik Muhammad Saad, Mickaël Coustaty, Nadeem Salamat, & V. B. Surya Prasath. (2018). SentiML ++: an extension of the SentiML sentiment annotation scheme. New Review of Hypermedia and Multimedia. 24(1). 28–43. 6 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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