Michel Buffa

1.0k citations
29 papers · 228 · h-index 8

Impact in

Papers in

Michel Buffa

23 papers receiving 202 citations

Peers

Michel Buffa
Comparison fields: 5 of 72
  • Communication 35
  • Computer Science Applications 25
  • Computer Vision and Pattern Recognition 59
  • Information Systems 64
  • Artificial Intelligence 83
Replace Oshani Seneviratne with:
Oshani Seneviratne United States
Cássio Prazeres Brazil
Igor Čavrak Croatia
Xianghang Mi United States
Yasuyuki Tahara Japan
Amel Bouzeghoub France
Amitoj Singh India
Ahmad Zainul Fanani Indonesia
T. V. Geetha India
Mike P. Wittie United States
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Citations per field
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Citations per year

Countries citing papers authored by Michel Buffa

Since Specialization
Citations

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

Fields of papers citing papers by Michel Buffa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michel Buffa, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michel Buffa Line = papers co-authored together Michel Buffa links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200785
2 200226
3 201521
4 200218
5 202015
6 201113
7
Using a Semantic Wiki in Communities of Practice
200810
8 20028
9 20067
10 20226
11
A Complete Navigation System for a Mobile Robot, Using Real-Time Stereovision and the Delaunay Triangulation.
19923
12 20223
13 19932
14 20222
15
Du Web aux wikis : une histoire des outils collaboratifs
20081
16 20201
17 20161
18 20141
19 20231
20 20241

About Michel Buffa

Michel Buffa is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems, Communication and Signal Processing, having authored 29 papers that have together received 228 indexed citations. Recurring topics across this work include Music Technology and Sound Studies (6 papers), Music and Audio Processing (6 papers), Semantic Web and Ontologies (6 papers), Wikis in Education and Collaboration (6 papers), Robotics and Sensor-Based Localization (5 papers), Robotic Path Planning Algorithms (4 papers), Natural Language Processing Techniques (3 papers) and Advanced Vision and Imaging (3 papers). The work is most often cited by research in Communication (35 citations), Computer Science Applications (25 citations), Computer Vision and Pattern Recognition (59 citations), Information Systems (64 citations) and Artificial Intelligence (83 citations). Michel Buffa has collaborated with scholars based in France, Italy and United States. Frequent co-authors include Fabien Gandon, Guillaume Erétéo, Peter Sander, Catherine Faron Zucker, Laurent Robert, Martial Hebert, M. Castillo, B. Güamis, Olivier Faugeras and D.J. O’Callaghan. Their work appears in journals such as Journal of the Audio Engineering Society, Language Resources and Evaluation, Dairy Science and Technology, Machine Vision and Applications and Postharvest Biology and Technology.

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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