Karin Schnass

1.4k citations
22 papers · 812 · h-index 10

Impact in

    • Sparse and Compressive Sensing Techniques
    • Blind Source Separation Techniques
    • Speech and Audio Processing
    • Direction-of-Arrival Estimation Techniques

Papers in

Karin Schnass

22 papers receiving 763 citations

Peers

Karin Schnass
Comparison fields: 5 of 63
  • Computational Mechanics 626
  • Signal Processing 308
  • Acoustics and Ultrasonics 21
  • Computational Mathematics 8
  • Computer Vision and Pattern Recognition 260
Replace Patrick Kuppinger with:
Patrick Kuppinger Switzerland
Rayan Saab United States
Song Li China
Guangwu Xu United States
Jeffrey D. Blanchard United States
Nam H. Nguyen United States
Gil Raz United States
Badri Narayan Bhaskar United States
Michael Davies United Kingdom
Kiryung Lee United States
Karin Schnass relative to Patrick Kuppinger Switzerland Patrick Kuppinger's profile →
Citations per field
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Citations per year

Countries citing papers authored by Karin Schnass

Since Specialization
Citations

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

Fields of papers citing papers by Karin Schnass

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 7 scholars most cited alongside Karin Schnass, 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 Karin Schnass Line = papers co-authored together Karin Schnass links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008366
2 2008101
3 201081
4 200876
5 200747
6 201237
7 201434
8 200713
9 20089
10 20089
11 20117
12 20186
13 20226
14 20105
15 20185
16 20232
17 20072
18 20172
19 20081
20 20071

About Karin Schnass

Karin Schnass is a scholar working on Computational Mechanics, Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications, having authored 22 papers that have together received 812 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (21 papers), Blind Source Separation Techniques (12 papers), Image and Signal Denoising Methods (8 papers), Microwave Imaging and Scattering Analysis (3 papers), Distributed Sensor Networks and Detection Algorithms (3 papers), Machine Learning and Algorithms (2 papers), Ultrasonics and Acoustic Wave Propagation (2 papers) and Advanced Image Processing Techniques (2 papers). The work is most often cited by research in Computational Mechanics (626 citations), Signal Processing (308 citations), Acoustics and Ultrasonics (21 citations), Computational Mathematics (8 citations) and Computer Vision and Pattern Recognition (260 citations). Karin Schnass has collaborated with scholars based in Switzerland, Austria and France. Frequent co-authors include Pierre Vandergheynst, Holger Rauhut, Rémi Gribonval, Jan Vybíral, Massimo Fornasier, Boris Mailhé and Pascal Frossard. Their work appears in journals such as IEEE Signal Processing Letters, IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, Journal of Fourier Analysis and Applications and Applied and Computational Harmonic Analysis.

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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