Florian Bordes
Impact in
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- Computational Geometry and Mesh Generation
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- Generative Adversarial Networks and Image Synthesis
- Multimodal Machine Learning Applications
- Video Analysis and Summarization
- Advanced Image and Video Retrieval Techniques
Papers in
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- Generative Adversarial Networks and Image Synthesis 2
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- Anomaly Detection Techniques and Applications 1
- Explainable Artificial Intelligence (XAI) 1
- Machine Learning in Healthcare 1
- Natural Language Processing Techniques 1
- Topic Modeling 1
- Computational Physics and Python Applications 1
- Co-authors
- Sina Honari (1 shared paper)Pascal Vincent (2 shared papers)Jack Urbanek (1 shared paper)Vasu Sharma (1 shared paper)Mary Williamson (1 shared paper)Timothée Lesort (1 shared paper)Yoshua Bengio (1 shared paper)David Filliat (1 shared paper)
- Journals
- arXiv (Cornell University) (1 paper)
In The Last Decade
Florian Bordes
4 papers receiving 13 citations
Peers
Comparison fields: 5 of 6
- Computer Graphics and Computer-Aided Design 2
- Computer Vision and Pattern Recognition 10
- Control and Systems Engineering 3
- Artificial Intelligence 3
- Computational Mechanics 1
Countries citing papers authored by Florian Bordes
This map shows the geographic impact of Florian Bordes'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 Florian Bordes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Florian Bordes more than expected).
Fields of papers citing papers by Florian Bordes
This network shows the impact of papers produced by Florian Bordes. 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 Florian Bordes. The network helps show where Florian Bordes may publish in the future.
Co-authors
The 9 scholars most cited alongside Florian Bordes, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 6 | |
| 2 | 2024 | 5 | |
| 3 | Evaluation of generative networks through their data augmentation capacity | 2018 | 1 |
| 4 | Iteratively unveiling new regions of interest in Deep Learning models | 2018 | 1 |
About Florian Bordes
Florian Bordes is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Radiology, Nuclear Medicine and Imaging and Infectious Diseases, having authored 4 papers that have together received 13 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (2 papers), Anomaly Detection Techniques and Applications (1 paper), COVID-19 diagnosis using AI (1 paper), Explainable Artificial Intelligence (XAI) (1 paper), Machine Learning in Healthcare (1 paper), Natural Language Processing Techniques (1 paper), Topic Modeling (1 paper) and Computational Physics and Python Applications (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (2 citations), Computer Vision and Pattern Recognition (10 citations), Control and Systems Engineering (3 citations), Artificial Intelligence (3 citations) and Computational Mechanics (1 citation). Florian Bordes has collaborated with scholars based in Canada and Portugal. Frequent co-authors include Sina Honari, Pascal Vincent, Jack Urbanek, Vasu Sharma, Mary Williamson, Timothée Lesort, Yoshua Bengio, David Filliat and Lisa Di Jorio. Their work appears in journals such as 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.