Moez Baccouche
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Biomedical Engineering
- Cognitive Neuroscience
- Co-authors
- Jean‐Luc DugelayGrigory AntipovSid-Ahmed BerraniCharles‐Edmond BichotMingyuan JiuJulien MilleChristophe GarcíaChristian Wolf
- Topics
- Face recognition and analysis (3 papers)Speech and Audio Processing (2 papers)Generative Adversarial Networks and Image Synthesis (2 papers)
- Journals
- Pattern RecognitionComputer Vision and Image UnderstandingarXiv (Cornell University)
- Partner nations
- FranceSouth KoreaTürkiye
In The Last Decade
Moez Baccouche
6 papers receiving 467 citations
Hit Papers
Peers
Comparison fields: 5 of 76
- Computer Vision and Pattern Recognition 377
- Artificial Intelligence 115
- Signal Processing 68
- Biomedical Engineering 20
- Cognitive Neuroscience 19
Countries citing papers authored by Moez Baccouche
This map shows the geographic impact of Moez Baccouche'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 Moez Baccouche with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Moez Baccouche more than expected).
Fields of papers citing papers by Moez Baccouche
This network shows the impact of papers produced by Moez Baccouche. 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 Moez Baccouche. The network helps show where Moez Baccouche may publish in the future.
Co-authorship network of co-authors of Moez Baccouche
This figure shows the co-authorship network connecting the top 25 collaborators of Moez Baccouche. A scholar is included among the top collaborators of Moez Baccouche 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 Moez Baccouche. Moez Baccouche is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 95 | |
| 3 | Face aging with conditional generative adversarial networksbreakdown → | 327 |
| 4 | Boosting face recognition via neural Super-Resolution. | 1 |
| 5 | 51 | |
| 6 | 4 |
About Moez Baccouche
Moez Baccouche is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 6 papers that have together received 486 indexed citations. Recurring topics across this work include Face recognition and analysis (3 papers), Speech and Audio Processing (2 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (377 citations), Signal Processing (68 citations) and Artificial Intelligence (115 citations). Moez Baccouche has collaborated with scholars based in France, South Korea and Türkiye. Frequent co-authors include Jean‐Luc Dugelay, Grigory Antipov, Sid-Ahmed Berrani, Charles‐Edmond Bichot, Mingyuan Jiu, Julien Mille, Christophe García, Christian Wolf, Oya Çeliktutan and Eric Lombardi. Their work appears in journals such as Pattern Recognition, Computer Vision and Image Understanding and arXiv (Cornell University).
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.