Boris Mailhé
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computational Mechanics top 10%
- Signal Processing top 10%
- Biomedical Engineering
- Co-authors
- Pierre VandergheynstRémi GribonvalTommaso MansiNicholas AyacheJulian KrebsHervé DelingetteFrédéric BimbotMark D. Plumbley
- Topics
- Sparse and Compressive Sensing Techniques (12 papers)Image and Signal Denoising Methods (9 papers)Blind Source Separation Techniques (9 papers)
- Cited by
- Computer Vision and Pattern RecognitionSignal ProcessingRadiology, Nuclear Medicine and Imaging
- Journals
- IEEE Transactions on Information TheoryIEEE Transactions on Image ProcessingMagnetic Resonance in Medicine
- Partner nations
- United StatesFranceSwitzerland
In The Last Decade
Boris Mailhé
22 papers receiving 386 citations
Peers
Comparison fields: 5 of 66
- Computer Vision and Pattern Recognition 177
- Radiology, Nuclear Medicine and Imaging 157
- Computational Mechanics 122
- Signal Processing 83
- Biomedical Engineering 66
Countries citing papers authored by Boris Mailhé
This map shows the geographic impact of Boris Mailhé'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 Boris Mailhé with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Boris Mailhé more than expected).
Fields of papers citing papers by Boris Mailhé
This network shows the impact of papers produced by Boris Mailhé. 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 Boris Mailhé. The network helps show where Boris Mailhé may publish in the future.
Co-authorship network of co-authors of Boris Mailhé
This figure shows the co-authorship network connecting the top 25 collaborators of Boris Mailhé. A scholar is included among the top collaborators of Boris Mailhé 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 Boris Mailhé. Boris Mailhé is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 9 | |
| 5 | 0 | |
| 6 | 19 | |
| 7 | Approximate message passing with a colored aliasing model for variable density Fourier sampled images | 9 |
| 8 | 37 | |
| 9 | 6 | |
| 10 | 15 | |
| 11 | 2 | |
| 12 | 2 | |
| 13 | 41 | |
| 14 | 22 | |
| 15 | 35 | |
| 16 | 15 | |
| 17 | 2 | |
| 18 | 35 | |
| 19 | 13 | |
| 20 | 1 |
About Boris Mailhé
Boris Mailhé is a scholar working on Acoustics and Ultrasonics, Signal Processing and Computational Mechanics, having authored 24 papers that have together received 394 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (12 papers), Image and Signal Denoising Methods (9 papers) and Blind Source Separation Techniques (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (177 citations), Signal Processing (83 citations) and Radiology, Nuclear Medicine and Imaging (157 citations). Boris Mailhé has collaborated with scholars based in United States, France and Switzerland. Frequent co-authors include Pierre Vandergheynst, Rémi Gribonval, Tommaso Mansi, Nicholas Ayache, Julian Krebs, Hervé Delingette, Frédéric Bimbot, Mark D. Plumbley, Daniele Barchiesi and Mariappan S. Nadar. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Image Processing and Magnetic Resonance in Medicine.
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.