J. Laroche

1.1k citations
35 papers · 734 · h-index 15

Impact in

Papers in

J. Laroche

30 papers receiving 608 citations

Peers

J. Laroche
Comparison fields: 5 of 76
  • Signal Processing 536
  • Computer Vision and Pattern Recognition 270
  • Aquatic Science 44
  • Artificial Intelligence 174
  • Computational Mechanics 99
Replace Jean Laroche with:
Jean Laroche France
Young-Cheol Park South Korea
Haohe Liu United Kingdom
Sebastian Böck Austria
Eva Cheng Australia
Haitao Liu China
Tomohiko Yamada United States
J.J. van Hees Germany
Robert C. Maher United States
J. Laroche relative to Jean Laroche France Jean Laroche's profile →
Citations per field
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Jean Laroche · 1×
Citations per year

Countries citing papers authored by J. Laroche

Since Specialization
Citations

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

Fields of papers citing papers by J. Laroche

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside J. Laroche, 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 J. Laroche Line = papers co-authored together J. Laroche links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999174
2 1993100
3 199450
4 200346
5 200342
6 200238
7 200236
8 200234
9 200727
10 200225
11 200620
12 201019
13 200218
14 200317
15 200416
16 199514
17 200410
18 20009
19 19927
20 19914

About J. Laroche

J. Laroche is a scholar working on Signal Processing, Computational Mechanics, Computer Vision and Pattern Recognition, Molecular Biology and Nature and Landscape Conservation, having authored 35 papers that have together received 734 indexed citations. Recurring topics across this work include Speech and Audio Processing (20 papers), Music and Audio Processing (12 papers), Advanced Adaptive Filtering Techniques (10 papers), Music Technology and Sound Studies (7 papers), Fish Ecology and Management Studies (3 papers), Genetic diversity and population structure (2 papers), Acoustic Wave Phenomena Research (2 papers) and Image and Signal Denoising Methods (2 papers). The work is most often cited by research in Signal Processing (536 citations), Computer Vision and Pattern Recognition (270 citations), Aquatic Science (44 citations), Artificial Intelligence (174 citations) and Computational Mechanics (99 citations). J. Laroche has collaborated with scholars based in France, United States and Canada. Frequent co-authors include Mark Dolson, Éric Moulines, Yannis Stylianou, Olivier Cappé, Michael M. Goodwin, Louis Quiniou, Justine Marchand, Arnaud Tanguy, Dario Moraga and Grégory Charrier. Their work appears in journals such as IEEE Transactions on Speech and Audio Processing, IEEE Transactions on Signal Processing, Marine Ecology Progress Series, Marine Environmental Research and Journal of Fish Biology.

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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