Maxime Bucher

3 papers and 126 indexed citations i.

About

Maxime Bucher is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Maxime Bucher has authored 3 papers receiving a total of 126 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 1 paper in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Maxime Bucher’s work include Domain Adaptation and Few-Shot Learning (3 papers), Multimodal Machine Learning Applications (2 papers) and COVID-19 diagnosis using AI (1 paper). Maxime Bucher is often cited by papers focused on Domain Adaptation and Few-Shot Learning (3 papers), Multimodal Machine Learning Applications (2 papers) and COVID-19 diagnosis using AI (1 paper). Maxime Bucher collaborates with scholars based in France. Maxime Bucher's co-authors include Tuan-Hung Vu, Matthieu Cord, Himalaya Jain, Gilles Puy, Alexandre Boulch, Renaud Marlet and Patrick Pérez and has published in prestigious journals such as Computer Vision and Image Understanding, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and 2021 International Conference on 3D Vision (3DV).

In The Last Decade

Co-authorship network of co-authors of Maxime Bucher i

Fields of papers citing papers by Maxime Bucher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Maxime Bucher

Since Specialization
Citations

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

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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2025