The lecture was delivered by Professor Serhii Anatoliiovych Babichev, Doctor of Technical Sciences and faculty member of the Department of Physics.
During the presentation, Professor Babichev introduced the audience to current challenges in the field of acoustic monitoring of surface objects and demonstrated innovative approaches to signal processing using wavelet transforms and machine learning algorithms. Particular attention was given to the development of an automated system capable of identifying ship types based on the spectral features of their acoustic signals.
The audience learned about the practical implementation of mathematical models, signal preprocessing techniques, classifier architecture, and training results. The lecture was accompanied by slides showcasing experimental data and computer modeling outcomes.
The lecturer also devoted special attention to the future prospects of the topic. It was noted that research in this area has significant potential for further development, especially in light of current challenges. Professor Babichev emphasized that, amid the ongoing war, developing drone detection systems based on acoustic signals has become increasingly relevant. Such a system, implemented as a mobile application, could provide timely alerts about approaching unmanned aerial vehicles, which is crucial for civilian safety.
We sincerely thank everyone who attended the lecture for their active participation and interest!
A recording of the lecture is available on our faculty's YouTube channel.
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