Rafał Zdunek
- Signal Processing top 0.5%
- Computer Vision and Pattern Recognition top 1%
- Computational Mathematics top 0.05%
- Computational Mechanics top 1%
- Artificial Intelligence top 2%
- Co-authors
- Andrzej CichockiШун-ичи АмариAnh Huy PhanConstantin PopaShengli XieZhaoshui HeGuoxu ZhouAndrzej Wołczowski
- Topics
- Sparse and Compressive Sensing Techniques (20 papers)Tensor decomposition and applications (20 papers)Blind Source Separation Techniques (18 papers)
In The Last Decade
Rafał Zdunek
62 papers receiving 3.0k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Signal Processing 1.1k
- Computer Vision and Pattern Recognition 807
- Computational Mathematics 788
- Computational Mechanics 757
- Artificial Intelligence 580
Countries citing papers authored by Rafał Zdunek
This map shows the geographic impact of Rafał Zdunek'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 Rafał Zdunek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rafał Zdunek more than expected).
Fields of papers citing papers by Rafał Zdunek
This network shows the impact of papers produced by Rafał Zdunek. 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 Rafał Zdunek. The network helps show where Rafał Zdunek may publish in the future.
Co-authorship network of co-authors of Rafał Zdunek
This figure shows the co-authorship network connecting the top 25 collaborators of Rafał Zdunek. A scholar is included among the top collaborators of Rafał Zdunek based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Rafał Zdunek. Rafał Zdunek is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 14 | |
| 7 | 17 | |
| 8 | 3 | |
| 9 | 7 | |
| 10 | 10 | |
| 11 | Local fault detection of rolling element bearing components by spectrogram clustering with semi-binary NMF | 22 |
| 12 | 17 | |
| 13 | 10 | |
| 14 | 6 | |
| 15 | 3 | |
| 16 | 154 | |
| 17 | Damped Newton Iterations for Nonnegative Matrix Factorization | 2 |
| 18 | 34 | |
| 19 | 11 | |
| 20 | 71 |
About Rafał Zdunek
Rafał Zdunek is a scholar working on Computational Mathematics, Signal Processing and Computational Mechanics, having authored 67 papers that have together received 3.1k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (20 papers), Tensor decomposition and applications (20 papers) and Blind Source Separation Techniques (18 papers). The work is most often cited by research in Computational Mathematics (788 citations), Signal Processing (1.1k citations) and Computer Vision and Pattern Recognition (807 citations). Rafał Zdunek has collaborated with scholars based in Poland, Japan and Italy. Frequent co-authors include Andrzej Cichocki, Шун-ичи Амари, Anh Huy Phan, Constantin Popa, Shengli Xie, Zhaoshui He, Guoxu Zhou, Andrzej Wołczowski, Zhaoshui He and Robert J. Plemmons. Their work appears in journals such as IEEE Transactions on Signal Processing, Sensors and IEEE Transactions on Industrial Informatics.
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.