David Brie

1.9k citations
81 papers · 1.2k · h-index 19

Impact in

Papers in

David Brie

80 papers receiving 1.2k citations

Peers

David Brie
Comparison fields: 5 of 129
  • Computational Mathematics 87
  • Signal Processing 274
  • Media Technology 198
  • Computational Mechanics 248
  • Computer Vision and Pattern Recognition 221
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Tsung‐Han Chan Taiwan
Zhihui Zhu United States
Manya Afonso Portugal
Xue Jiang China
Matan Gavish Israel
Houzhang Fang China
Lixing Han United States
Gilad Lerman United States
Ole Tingleff Denmark
Yiming Pi China
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Citations per field
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Citations per year

Countries citing papers authored by David Brie

Since Specialization
Citations

This map shows the geographic impact of David Brie'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 David Brie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Brie more than expected).

Fields of papers citing papers by David Brie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Brie. 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 David Brie. The network helps show where David Brie may publish in the future.

Co-authors

The 25 scholars most cited alongside David Brie, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Brie Line = papers co-authored together David Brie links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201193
2 201191
3 200070
4 202062
5 199753
6 201153
7 201650
8 200650
9 202144
10 202332
11 200930
12 201530
13 201630
14 199729
15 200628
16 201227
17 201523
18 201222
19 201520
20 202018

About David Brie

David Brie is a scholar working on Computational Mechanics, Signal Processing, Computer Vision and Pattern Recognition, Computational Mathematics and Media Technology, having authored 81 papers that have together received 1.2k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (21 papers), Blind Source Separation Techniques (21 papers), Image and Signal Denoising Methods (17 papers), Tensor decomposition and applications (12 papers), Spectroscopy and Chemometric Analyses (11 papers), Advanced Image Fusion Techniques (9 papers), Speech and Audio Processing (9 papers) and Advanced Adaptive Filtering Techniques (8 papers). The work is most often cited by research in Computational Mathematics (87 citations), Signal Processing (274 citations), Media Technology (198 citations), Computational Mechanics (248 citations) and Computer Vision and Pattern Recognition (221 citations). David Brie has collaborated with scholars based in France, China and United States. Frequent co-authors include Charles Soussen, Sébastian Miron, Jérôme Idier, Junbo Duan, Saïd Moussaoui, Konstantin Usevich, Xijing Guo, Pierre Comon, Tom L. Richard and El‐Hadi Djermoune. Their work appears in journals such as IEEE Transactions on Signal Processing, Signal Processing, Chemometrics and Intelligent Laboratory Systems, IEEE Signal Processing Letters and Mechanical Systems 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.

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