Peter Karsmakers

1.4k citations
59 papers · 916 indexed · h-index 16

Impact in

Papers in

Peter Karsmakers

52 papers receiving 883 citations

Peers

Peter Karsmakers
Comparison fields: 5 of 122
  • Signal Processing 249
  • Computer Vision and Pattern Recognition 216
  • Computational Mathematics 4
  • Biomedical Engineering 291
  • Artificial Intelligence 199
Replace Roberto Gil‐Pita with:
Roberto Gil‐Pita Spain
Mingjiang Wang China
Risanuri Hidayat Indonesia
Yunho Jung South Korea
Yun Pan China
M. J. E. Salami Malaysia
Phuc Nguyen United States
Francesco Beritelli Italy
Takumi Kobayashi Japan
Ali Hassan Pakistan
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Citations per field
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Citations per year

Countries citing papers authored by Peter Karsmakers

Since Specialization
Citations

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

Fields of papers citing papers by Peter Karsmakers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1
LS-SVMlab Toolbox User's Guide version 1.7
2010145
2 2013144
3 201475
4 201366
5
The SINS database for detection of daily activities in a home environment using an Acoustic Sensor Network
201759
6 201352
7 200741
8 201234
9
Automatic in-door fall detection based on microwave radar measurements
201232
10 201326
11 200925
12 201322
13 201119
14
Automatic Monitoring of Activities of Daily Living based on Real-life Acoustic Sensor Data: a~preliminary study
201317
15 201917
16 201116
17 202410
18 200710
19 20259
20 20238

About Peter Karsmakers

Peter Karsmakers is a scholar working on Biomedical Engineering, Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence and Surgery, having authored 59 papers that have together received 916 indexed citations. Recurring topics across this work include Non-Invasive Vital Sign Monitoring (15 papers), Speech and Audio Processing (13 papers), Music and Audio Processing (12 papers), Healthcare Technology and Patient Monitoring (9 papers), Anomaly Detection Techniques and Applications (8 papers), Context-Aware Activity Recognition Systems (8 papers), Music Technology and Sound Studies (6 papers) and Advanced Chemical Sensor Technologies (4 papers). The work is most often cited by research in Signal Processing (249 citations), Computer Vision and Pattern Recognition (216 citations), Computational Mathematics (4 citations), Biomedical Engineering (291 citations) and Artificial Intelligence (199 citations). Peter Karsmakers has collaborated with scholars based in Belgium, Malaysia and United Kingdom. Frequent co-authors include Bart Vanrumste, Johan A. K. Suykens, Dominique Schreurs, Paul Leroux, M. Mercuri, Kristiaan Pelckmans, Hugo Van hamme, Ping Jack Soh, Guy A. E. Vandenbosch and Kris De Brabanter. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, IEEE Access, Machine Learning, Journal of the Audio Engineering Society and Artificial Intelligence 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.

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