Karin Schnass

24 papers and 798 indexed citations i.

About

Karin Schnass is a scholar working on Computational Mechanics, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Karin Schnass has authored 24 papers receiving a total of 798 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computational Mechanics, 14 papers in Signal Processing and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Karin Schnass’s work include Sparse and Compressive Sensing Techniques (23 papers), Blind Source Separation Techniques (14 papers) and Image and Signal Denoising Methods (9 papers). Karin Schnass is often cited by papers focused on Sparse and Compressive Sensing Techniques (23 papers), Blind Source Separation Techniques (14 papers) and Image and Signal Denoising Methods (9 papers). Karin Schnass collaborates with scholars based in Austria, Switzerland and France. Karin Schnass's co-authors include Pierre Vandergheynst, Holger Rauhut, Rémi Gribonval, Massimo Fornasier, Jan Vybíral, Valeriya Naumova and Boris Mailhé and has published in prestigious journals such as IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing and IEEE Signal Processing Letters.

In The Last Decade

Co-authorship network of co-authors of Karin Schnass i

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.

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).

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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2025