S. Osowski

171 papers receiving 3.4k citations

Peers

S. Osowski
Comparison fields: 5 of 147
  • Cardiology and Cardiovascular Medicine 929
  • Cognitive Neuroscience 806
  • Signal Processing 328
  • Artificial Intelligence 778
  • Computer Vision and Pattern Recognition 470
Replace Radek Martínek with:
Radek Martínek Czechia
Seán McLoone United Kingdom
Muhammad Arif Pakistan
Lars Karlsson Sweden
Jiuwen Cao China
Guijin Wang China
Osama Abdeljaber Qatar
Moongu Jeon South Korea
Elif Derya Übeylı Türkiye
Feng Jiang China
S. Osowski relative to Radek Martínek Czechia Radek Martínek's profile →
Citations per field
00.5×2.9×
Radek Martínek · 1×
Citations per year

Countries citing papers authored by S. Osowski

Since Specialization
Citations

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

Fields of papers citing papers by S. Osowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 192 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001399
2 2004396
3 2006161
4 2004152
5 2003134
6 1992120
7 201192
8 200888
9 201183
10 201274
11 200270
12 200965
13 200258
14 201656
15 200953
16 202152
17 199652
18
MLP and SVM networks - a comparative study
200451
19 200551
20 200648

About S. Osowski

S. Osowski is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Biomedical Engineering and Control and Systems Engineering, having authored 192 papers that have together received 3.6k indexed citations. Recurring topics across this work include Neural Networks and Applications (43 papers), Advanced Chemical Sensor Technologies (18 papers), AI in cancer detection (17 papers), Energy Load and Power Forecasting (17 papers), Gene expression and cancer classification (12 papers), Digital Imaging for Blood Diseases (12 papers), Image and Signal Denoising Methods (11 papers) and Sensor Technology and Measurement Systems (11 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (929 citations), Cognitive Neuroscience (806 citations), Signal Processing (328 citations), Artificial Intelligence (778 citations) and Computer Vision and Pattern Recognition (470 citations). S. Osowski has collaborated with scholars based in Poland, Japan and Vietnam. Frequent co-authors include Trần Hoài Linh, Tomasz Markiewicz, Krzysztof Siwek, K. Brudzewski, Robert Sałat, Jarosław Kurek, Bartosz Świderski, Michał Kruk, Andrzej Cichocki and Andrzej Rysz. Their work appears in journals such as Electronics Letters, Bulletin of the Polish Academy of Sciences Technical Sciences, Expert Systems with Applications, IEEE Transactions on Instrumentation and Measurement and Sensors and Actuators B Chemical.

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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