Frédéric Andrès
Impact in
- Sensory Systems top 10%
- Olfactory and Sensory Function Studies
Papers in
-
- Semantic Web and Ontologies 17
- Advanced Text Analysis Techniques 8
- Topic Modeling 7
-
- Video Analysis and Summarization 9
- Co-authors
- Xiangfeng Dai (3 shared papers)Gheorghiță Ghinea (7 shared papers)Stephen R. Gulliver (1 shared paper)Deepak Garg (1 shared paper)Irena Spasić (2 shared papers)Rajeev K. Agrawal (2 shared papers)Samuel Chapman (1 shared paper)Chutiporn Anutariya (5 shared papers)
- Journals
- IEEE Access (2 papers)Applied Sciences (2 papers)Lecture notes in computer science (11 papers)CoDAS (1 paper)Multimedia Tools and Applications (1 paper)
- Partner nations
- JapanFranceUnited States
In The Last Decade
Frédéric Andrès
85 papers receiving 643 citations
Peers
Comparison fields: 5 of 114
- Computational Mathematics 6
- Sensory Systems 39
- Computer Vision and Pattern Recognition 175
- Human-Computer Interaction 42
- Artificial Intelligence 224
Countries citing papers authored by Frédéric Andrès
This map shows the geographic impact of Frédéric Andrès'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 Frédéric Andrès with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frédéric Andrès more than expected).
Fields of papers citing papers by Frédéric Andrès
This network shows the impact of papers produced by Frédéric Andrès. 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 Frédéric Andrès. The network helps show where Frédéric Andrès may publish in the future.
Co-authors
The 25 scholars most cited alongside Frédéric Andrès, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 102 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 102 | |
| 2 | 2019 | 84 | |
| 3 | 2011 | 81 | |
| 4 | 2015 | 67 | |
| 5 | 2021 | 48 | |
| 6 | 2018 | 15 | |
| 7 | 2009 | 13 | |
| 8 | 1990 | 12 | |
| 9 | 2006 | 12 | |
| 10 | 2010 | 11 | |
| 11 | 2018 | 9 | |
| 12 | 2021 | 9 | |
| 13 | 2001 | 9 | |
| 14 | CyberBrain: Towards the Next Generation Social Intelligence | 2008 | 8 |
| 15 | 2012 | 8 | |
| 16 | 2006 | 7 | |
| 17 | Phasme: A High Performance Parallel Application-Oriented DBMS. | 1998 | 7 |
| 18 | A Visual Lexical Model of Caravanserais of Silk Roads, A Tool for Semantic Access to Architectural 3D Data. | 2004 | 7 |
| 19 | 2017 | 7 | |
| 20 | 2007 | 7 |
About Frédéric Andrès
Frédéric Andrès is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Information Systems and Computer Networks and Communications, having authored 102 papers that have together received 685 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (17 papers), Video Analysis and Summarization (9 papers), Advanced Database Systems and Queries (9 papers), Data Management and Algorithms (9 papers), Advanced Text Analysis Techniques (8 papers), Topic Modeling (7 papers), Web Data Mining and Analysis (6 papers) and Smart Agriculture and AI (5 papers). The work is most often cited by research in Computational Mathematics (6 citations), Sensory Systems (39 citations), Computer Vision and Pattern Recognition (175 citations), Human-Computer Interaction (42 citations) and Artificial Intelligence (224 citations). Frédéric Andrès has collaborated with scholars based in Japan, France and United States. Frequent co-authors include Xiangfeng Dai, Gheorghiță Ghinea, Stephen R. Gulliver, Deepak Garg, Irena Spasić, Rajeev K. Agrawal, Samuel Chapman, Chutiporn Anutariya, Asanee Kawtrakul and Sadhu Ramakrishnan Balasundaram. Their work appears in journals such as IEEE Access, Applied Sciences, Lecture notes in computer science, CoDAS and Multimedia Tools and Applications.
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.