J. Hérault

2.0k citations
36 papers · 1.3k · h-index 15

Impact in

Papers in

J. Hérault

33 papers receiving 1.2k citations

Peers

J. Hérault
Comparison fields: 5 of 104
  • Signal Processing 315
  • Computer Vision and Pattern Recognition 519
  • Media Technology 194
  • Analytical Chemistry 111
  • Artificial Intelligence 346
Replace B.J. Hosticka with:
B.J. Hosticka Germany
Thomas G. Stockham United States
Ramakrishnan Mukundan New Zealand
Yehoshua Y. Zeevi Israel
Martin Lades Germany
Christophe García France
Besma Abidi United States
S.S. Dlay United Kingdom
Gaetano Scarano Italy
Wesley E. Snyder United States
J. Hérault relative to B.J. Hosticka Germany B.J. Hosticka's profile →
Citations per field
00.5×4.8×
B.J. Hosticka · 1×
Citations per year

Countries citing papers authored by J. Hérault

Since Specialization
Citations

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

Fields of papers citing papers by J. Hérault

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside J. Hérault, 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. Hérault Line = papers co-authored together J. Hérault links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997402
2 2005229
3 1986106
4
Detection de grandeurs primitives dans un message composite par une architecture de calcul neuromimetique en apprentissage non supervise
1985100
5 200289
6 201062
7 201056
8 199925
9 199624
10 198924
11 200823
12 201116
13 201215
14 200915
15 201514
16 200913
17 20029
18 20008
19 20088
20
A Contrast and Motion-Sensitive Silicon Retina
19955

About J. Hérault

J. Hérault is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics and Cognitive Neuroscience, having authored 36 papers that have together received 1.3k indexed citations. Recurring topics across this work include Neural Networks and Applications (14 papers), Magnetic properties of thin films (8 papers), Advanced Memory and Neural Computing (7 papers), Blind Source Separation Techniques (5 papers), Neural dynamics and brain function (5 papers), CCD and CMOS Imaging Sensors (5 papers), Visual perception and processing mechanisms (5 papers) and Advanced Vision and Imaging (4 papers). The work is most often cited by research in Signal Processing (315 citations), Computer Vision and Pattern Recognition (519 citations), Media Technology (194 citations), Analytical Chemistry (111 citations) and Artificial Intelligence (346 citations). J. Hérault has collaborated with scholars based in France, Italy and Switzerland. Frequent co-authors include Sabine Süsstrunk, Dawn E. Alley, Christian Jutten, Giansalvo Cirrincione, Sabine Van Huffel, Maurizio Cirrincione, Barthélémy Durette, Alexandre Benoît, Alice Caplier and Antonio Torralba. Their work appears in journals such as Neurocomputing, IEEE Transactions on Magnetics, Perception, Applied Physics Letters and Neural Processing Letters.

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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