A little socializer of AGH’s Signal Processing group to Zakopane …
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Signal Processing Group
Welcome to the AGH Signal Processing Group
The Signal Processing Group is part of the Institute of Electronics, which belongs to the Faculty of Computer Science, Electronics and Telecommunications at AGH University of Krakow, Poland. Group members perform research into various aspects of digital signal processing (DSP) focusing mainly on speech and audio signal processing for the Internet of Things (IoT), multimedia and communication applications, as well as the processing of biomedical signals and audio-video for virtual and augmented reality. Research into signal processing builds upon an intelligent integration of classical DSP techniques, statistical signal processing and machine learning.
The Signal Processing Group is led by Associate Professor Konrad Kowalczyk and it consists of over a dozen of the members of academic staff and research students at a Ph.D. level. The DSP team collaborates internationally with renown academic partners and nationally with the local high-tech industry, and has successfully completed a number of research and commercial R&D projects. The group offers fundamental and advanced taught courses on signal processing, DSP, machine learning, and programming for embedded and multimedia applications at both undergraduate and graduate levels. The Signal Processing Group regularly offers student jobs in research and R&D projects, as well as provides a breadth of opportunities for thesis work and student internships.
We are very happy that 3 papers authored by members of AGH Signal Processing Group were accepted for presentation at IEEE ICASSP 2022 conference. Stanisław Kacprzak, Magdalena Rybicka, Konrad Kowalczyk, “Spoken Language Recognition with Cluster-based Modeling“, accepted for IEEE ICASSP 2022. Mieszko Fraś, Marcin Witkowski, Konrad Kowalczyk, “Convolutional Weighted Minimum Mean Square Error Filter for […]
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Our PhD student mgr inż. Magdalena Rybicka has been nominated for the Fulbright Junior Research Award 2022-23. She will spend the next academic year at the Center for Language and Speech Processing at Johns Hopkins University in Baltimore, where she will conduct part of her PhD research. We are very proud of Magda to be […]
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Join us at IEEE Intternational Workshop on Multimedia Signal Processing 2021 to be held in Tampere, Finland, where Julitta Bartolewska and Mateusz Guzik will give in-person presentations: Incorporation of Localization Information for Sound Source Separation in Spherical Harmonic Domain by Mateusz Guzik, Mieszko Fraś, and Konrad Kowalczyk during the session on Friday, October 8, 8:30-9:30. […]
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Join us at INTERSPEECH 2021 conference in Brno, where Magdalena Rybicka and Mieszko Fraś will give 2 in-person oral presentations on: Spine2Net: SpineNet with Res2Net and Time-Squeeze-and-Excitation Blocks for Speaker Recognition by Magdalena Rybicka, Jesús Villalba, Piotr Żelasko, Najim Dehak, and Konrad Kowalczyk during the session: Embedding and Network Architecture for Speaker Recognition on Tuesday, […]
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Join AGH Signal Processing group at the European Signal Processing Conference 2021 and visit 3 presentations by Stanisław Kacprzak, Marcin Witkowski, and former group member Daniel Krause on the outcome of two current projects MLSAP and APDAS: Stanisław Kacprzak will talk about Adversarial Domain Adaptation with Paired Examples for Acoustic Scene Classification on Different Recording […]
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We are proud to announce that TEAM AGH consisting of our 4 highly talented undergraduate students: Michał Antos, Aleksander Strzeboński, Piotr Radecki, Mateusz Wojtulewicz, organized and led by a tutor mgr inż. Szymon Woźniak, won the second prize (1st runner up) in the IEEE Signal Processing Cup 2021 (SP Cup 2021) student competition. This year’s […]
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We are very happy that members of AGH Signal Processing Group will be present at this year’s IEEE ICASSP. On Thursday, 10 June, at 13:00 – 13:45 (Eastern Daylight Time) mgr inż. Mieszko Fraś will present the paper entitled: “Maximum a Posteriori Estimator for Convolutive Sound Source Separation with Sub-Source Based NTF Model and the […]
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