Max Mignotte

4.7k total citations · 1 hit paper
147 papers, 3.1k citations indexed

About

Max Mignotte is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Max Mignotte has authored 147 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Computer Vision and Pattern Recognition, 38 papers in Media Technology and 22 papers in Artificial Intelligence. Recurrent topics in Max Mignotte's work include Medical Image Segmentation Techniques (49 papers), Remote-Sensing Image Classification (28 papers) and Image Retrieval and Classification Techniques (19 papers). Max Mignotte is often cited by papers focused on Medical Image Segmentation Techniques (49 papers), Remote-Sensing Image Classification (28 papers) and Image Retrieval and Classification Techniques (19 papers). Max Mignotte collaborates with scholars based in Canada, France and United States. Max Mignotte's co-authors include Lazhar Khelifi, Redha Touati, Patrick Pérez, Patrick Bouthémy, C. Collet, Mohamed Dahmane, Jean Meunier, S. Benameur, Jacques A. de Guise and Pierre‐Marc Jodoin and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, NeuroImage and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Max Mignotte

141 papers receiving 2.9k citations

Hit Papers

Deep Learning for Change Detection in Remote Sensing Imag... 2020 2026 2022 2024 2020 50 100 150 200 250

Peers

Max Mignotte
Comparison fields: 5 of 131
  • Computer Vision and Pattern Recognition 1.4k
  • Media Technology 1.1k
  • Artificial Intelligence 521
  • Atmospheric Science 416
  • Biomedical Engineering 338
Replace Min Wang with:
Min Wang China
Pierre Alliez France
Henri Maı̂tre France
Guillaume Charpiat France
Chandra Kambhamettu United States
Anthony Yezzi United States
Jean‐Yves Tourneret France
Laurent Najman France
Hamid Krim United States
S. Sternberg United States
Min Wang China View profile →
Citations per field, relative to Max Mignotte
Max Mignotte · 1×
Citations per year, relative to Max Mignotte
Max Mignotte · 1×

Countries citing papers authored by Max Mignotte

Since Specialization
Citations

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

Fields of papers citing papers by Max Mignotte

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Max Mignotte

This figure shows the co-authorship network connecting the top 25 collaborators of Max Mignotte. A scholar is included among the top collaborators of Max Mignotte 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 Max Mignotte. Max Mignotte 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
# Work Indexed citations
1 0
2 1
3 5
4 14
5 2
6 157
7 13
8 80
9 8
10
Unsupervised Statistical Method for Edgel Clustering With Applications to Shape Localization.
1
11 196
12 22
13 6
14 11
15 17
16 0
17
An inequality on the greates roots of a polynomial.
1
18
Statistiques sur $\mathbb {F}_q [X]$
1
19 15
20 78

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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