A week after the conclusion of the INTERNOISE 2024 conference, we are still deeply impressed by this unforgettable experience. The conference brought together nearly 2,000 participants from around the world to share their knowledge, opinions, and innovative approaches in the field of acoustics.
The variety of contributions from research and technological innovations provided attendees with a comprehensive picture of the future of acoustics. Speakers and participants enthusiastically shared their insights and experiences, creating an inspiring atmosphere for generating new ideas and finding solutions to the challenges the industry faces. Such gatherings are invaluable, as they foster the exchange of ideas and networking, undoubtedly accelerating the development of the field.
Our team presented a research paper titled “Comparative Analysis of CNN and TNN Models in Environmental Noise Source Identification.” In this study, we compared Convolutional Neural Networks (CNN) and Transformer Neural Networks (TNN) to enhance the accuracy and efficiency of noise source identification using artificial intelligence, enabling faster analysis of measurements and better noise management strategies in urban environments.
Check out the full research paper, available with an in-depth analysis of results and insight into our methodology, by clicking the link below!
A huge thank you and congratulations to the exceptional organizers who, with their dedication, professionalism, and effort, ensured the event ran smoothly, allowing us to focus on the content that brought us together. Once again, THANK YOU!
