Stéphane Maes

3.4k citations
40 papers · 378 · h-index 9

Impact in

Papers in

Stéphane Maes

36 papers receiving 346 citations

Peers

Stéphane Maes
Comparison fields: 5 of 62
  • Signal Processing 146
  • Computer Vision and Pattern Recognition 97
  • Control and Systems Engineering 102
  • Artificial Intelligence 139
  • Information Systems 79
Replace Milan Milosavljević with:
Milan Milosavljević Serbia
D.J. Sebald United States
Xiaohui Yang China
Tianmeng Yang China
Babak Nasersharif Iran
Zhangqing He China
Minkyu Choi South Korea
Zachary Zimmerman United States
Stéphane Maes relative to Milan Milosavljević Serbia Milan Milosavljević's profile →
Citations per field
00.5×2×3×4.1×
Milan Milosavljević · 1×
Citations per year

Countries citing papers authored by Stéphane Maes

Since Specialization
Citations

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

Fields of papers citing papers by Stéphane Maes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017140
2 200126
3 200720
4 200217
5 200317
6 200013
7 199713
8 200212
9 20009
10 20028
11 20038
12 20017
13 20027
14 19957
15 20027
16 20016
17 20026
18 19946
19
A Speech Biometrics System with Multi- Grained Speaker Modeling
20004
20 20024

About Stéphane Maes

Stéphane Maes is a scholar working on Artificial Intelligence, Signal Processing, Information Systems, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 40 papers that have together received 378 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (13 papers), Speech and Audio Processing (13 papers), Service-Oriented Architecture and Web Services (11 papers), Speech and dialogue systems (7 papers), Music and Audio Processing (6 papers), Image and Signal Denoising Methods (5 papers), Mobile Agent-Based Network Management (5 papers) and Context-Aware Activity Recognition Systems (3 papers). The work is most often cited by research in Signal Processing (146 citations), Computer Vision and Pattern Recognition (97 citations), Control and Systems Engineering (102 citations), Artificial Intelligence (139 citations) and Information Systems (79 citations). Stéphane Maes has collaborated with scholars based in United States, Belgium and China. Frequent co-authors include Ingrid Daubechies, Homayoon Beigi, Jiří Navrátil, T. V. Raman, Jeffrey Sorensen, Upendra V. Chaudhari, Ramesh A. Gopinath, Daby Sow, Chatschik Bisdikian and Jan Kleindienst. Their work appears in journals such as SIAM Journal on Applied Mathematics, IEEE Wireless Communications, IEEE Transactions on Speech and Audio Processing, The Journal of the Acoustical Society of America and Lecture notes in computer science.

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.

Explore authors with similar magnitude of impact