Thibaut Durand

1.1k citations
9 papers · 150 indexed · h-index 6
Topics
Advanced Image and Video Retrieval Techniques (3 papers)Multimodal Machine Learning Applications (3 papers)Image Retrieval and Classification Techniques (2 papers)
Partner nations
FranceCanadaAustria

In The Last Decade

Thibaut Durand

9 papers receiving 146 citations

Peers

Thibaut Durand
Comparison fields: 5 of 60
  • Computer Vision and Pattern Recognition 79
  • Artificial Intelligence 29
  • Soil Science 17
  • Computer Graphics and Computer-Aided Design 17
  • Ecology 13
Replace De Xie with:
De Xie China
Julien Mille France
Ralf Nagel Germany
Xiang An China
Ziyan Wang China
Damayanthi Herath Sri Lanka
Chaotao Ding China
Ilya A. Petrov Germany
Ping Luo China
Thibaut Durand relative to De Xie China De Xie's profile →
Citations per field
00.5×3.3×
De Xie · 1×
Citations per year

Countries citing papers authored by Thibaut Durand

Since Specialization
Citations

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

Fields of papers citing papers by Thibaut Durand

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thibaut Durand

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

All Works

9 of 9 papers shown
#WorkIndexed citations
1 28
2 6
3 65
4 22
5
Variational Selective Autoencoder
2
6 5
7 15
8 3
9 4

About Thibaut Durand

Thibaut Durand is a scholar working on Computer Vision and Pattern Recognition, Ecological Modeling and Media Technology, having authored 9 papers that have together received 150 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (3 papers), Multimodal Machine Learning Applications (3 papers) and Image Retrieval and Classification Techniques (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (17 citations), Computer Vision and Pattern Recognition (79 citations) and Soil Science (17 citations). Thibaut Durand has collaborated with scholars based in France, Canada and Austria. Frequent co-authors include Leonid Sigal, Greg Mori, Jiawei He, Matthieu Cord, Nicolas Thome, Margot Neyret, Anneke de Rouw, Jean‐Louis Janeau, Henri Robain and Christian Valentin. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks and Learning Systems and CATENA.

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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