Artur Janicki
- Signal Processing top 2%
- Speech and Audio Processing 10
- Music and Audio Processing 6
- Artificial Intelligence top 5%
- Internet Traffic Analysis and Secure E-voting 14
- Speech Recognition and Synthesis 12
- Topic Modeling 8
- Natural Language Processing Techniques 8
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- Advanced Steganography and Watermarking Techniques 12
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- Network Security and Intrusion Detection 8
Artur Janicki
42 papers receiving 454 citations
Peers
Comparison fields: 5 of 56
- Signal Processing 258
- Artificial Intelligence 313
- Computer Vision and Pattern Recognition 142
- Computer Networks and Communications 137
- Experimental and Cognitive Psychology 39
Countries citing papers authored by Artur Janicki
This map shows the geographic impact of Artur Janicki'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 Artur Janicki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Artur Janicki more than expected).
Fields of papers citing papers by Artur Janicki
This network shows the impact of papers produced by Artur Janicki. 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 Artur Janicki. The network helps show where Artur Janicki may publish in the future.
Co-authorship network
The 15 scholars most cited alongside Artur Janicki, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 5 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 6 | |
| 9 | 2022 | 18 | |
| 10 | 2022 | 26 | |
| 11 | 2020 | 82 | |
| 12 | 2017 | 3 | |
| 13 | 2015 | 8 | |
| 14 | Re-assessing the threat of replay spoofing attacks against automatic speaker verification | 2014 | 59 |
| 15 | 2014 | 1 | |
| 16 | Voice-Driven Computer Game in Noisy Environments. | 2013 | 2 |
| 17 | Automatic speech recognition for polish in a computer game interface | 2011 | 4 |
| 18 | Visual speech synthesis for Polish using keyframe based animation | 2010 | 0 |
| 19 | Głosowy PIN - uwierzytelnianie użytkownika z wykorzystaniem algorytmu weryfikacji mówcy | 2007 | 0 |
| 20 | Badanie jakości sygnału mowy w telefonii internetowej z wykorzystaniem zdań nieprzewidywalnych semantycznie | 2006 | 1 |
About Artur Janicki
Artur Janicki is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 49 papers that have together received 482 indexed citations. Recurring topics across this work include Internet Traffic Analysis and Secure E-voting (14 papers), Advanced Steganography and Watermarking Techniques (12 papers), Speech Recognition and Synthesis (12 papers), Speech and Audio Processing (10 papers), Topic Modeling (8 papers), Network Security and Intrusion Detection (8 papers), Natural Language Processing Techniques (8 papers) and Music and Audio Processing (6 papers). The work is most often cited by research in Signal Processing (258 citations), Artificial Intelligence (313 citations) and Computer Vision and Pattern Recognition (142 citations). Artur Janicki has collaborated with scholars based in Poland, France and Italy. Frequent co-authors include Wojciech Mazurczyk, Federico Alegre, Nicholas Evans, Krzysztof Szczypiorski, Katarzyna Wasielewska, Michał Choraś, Igino Corona, Marek Pawlicki, Luca Caviglione and Marek Kozłowski. Their work appears in journals such as Electronics, IEEE Access, Applied Sciences, Multimedia Tools and Applications and International Journal of Applied Mathematics and Computer Science.
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.