J.-C. Pesquet
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Computational Mechanics top 10%
- Signal Processing top 10%
- Computational Theory and Mathematics
- Co-authors
- Patrick L. CombettesAmel Benazza‐BenyahiaBéatrice Pesquet‐PopescuLuis M. Briceño-AriasNelly PustelnikMounir KaanicheMichel ParentAthina P. Petropulu
- Topics
- Image and Signal Denoising Methods (17 papers)Advanced Data Compression Techniques (9 papers)Digital Filter Design and Implementation (6 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingSignal Processing
- Partner nations
- FranceTunisiaUnited States
In The Last Decade
J.-C. Pesquet
22 papers receiving 270 citations
Peers
Comparison fields: 5 of 42
- Computer Vision and Pattern Recognition 224
- Media Technology 69
- Computational Mechanics 65
- Signal Processing 64
- Computational Theory and Mathematics 23
Countries citing papers authored by J.-C. Pesquet
This map shows the geographic impact of J.-C. Pesquet'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 J.-C. Pesquet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J.-C. Pesquet more than expected).
Fields of papers citing papers by J.-C. Pesquet
This network shows the impact of papers produced by J.-C. Pesquet. 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 J.-C. Pesquet. The network helps show where J.-C. Pesquet may publish in the future.
Co-authorship network of co-authors of J.-C. Pesquet
This figure shows the co-authorship network connecting the top 25 collaborators of J.-C. Pesquet. A scholar is included among the top collaborators of J.-C. Pesquet 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 J.-C. Pesquet. J.-C. Pesquet is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 6 | |
| 3 | 12 | |
| 4 | 39 | |
| 5 | 28 | |
| 6 | 23 | |
| 7 | 8 | |
| 8 | 1 | |
| 9 | 6 | |
| 10 | 0 | |
| 11 | 3 | |
| 12 | 26 | |
| 13 | 17 | |
| 14 | 31 | |
| 15 | 1 | |
| 16 | 50 | |
| 17 | 11 | |
| 18 | Wheezing Lung Sounds Analysis with adaptive local trigonometric transform. | 2 |
| 19 | 13 | |
| 20 | 1 |
About J.-C. Pesquet
J.-C. Pesquet is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Applied Mathematics, having authored 24 papers that have together received 292 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (17 papers), Advanced Data Compression Techniques (9 papers) and Digital Filter Design and Implementation (6 papers). The work is most often cited by research in Computational Mathematics (11 citations), Computer Vision and Pattern Recognition (224 citations) and Media Technology (69 citations). J.-C. Pesquet has collaborated with scholars based in France, Tunisia and United States. Frequent co-authors include Patrick L. Combettes, Amel Benazza‐Benyahia, Béatrice Pesquet‐Popescu, Luis M. Briceño-Arias, Nelly Pustelnik, Mounir Kaaniche, Michel Parent, Athina P. Petropulu, Ioannis Dologlou and Lotfi Chaâri. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Signal Processing.
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.