65 citations · 183 across the 27 of their papers we have counts for
4 papers · 2 filters
Physics-Informed Transfer Learning for Data-Driven Sound Source Reconstruction in Near-Field Acoustic Holography
Xinmeng Luan, Mirco Pezzoli, Fabio Antonacci +1
We propose a transfer learning framework for sound source reconstruction in Near-field Acoustic Holography (NAH), which adapts a well-trained data-driven model from one type of sou…
Low-Rank Adaptation of Deep Prior Neural Networks For Room Impulse Response Reconstruction
Mirco Pezzoli, Federico Miotello, Shoichi Koyama +1
The Deep Prior framework has emerged as a powerful generative tool which can be used for reconstructing sound fields in an environment from few sparse pressure measurements. It emp…
Physics-Informed Neural Network-Driven Sparse Field Discretization Method for Near-Field Acoustic Holography
Xinmeng Luan, Mirco Pezzoli, Fabio Antonacci +1
We propose the Physics-Informed Neural Network-driven Sparse Field Discretization method (PINN-SFD), a novel self-supervised, physics-informed deep learning approach for addressing…
Past, Present, and Future of Spatial Audio and Room Acoustics
Shoichi Koyama, Enzo De Sena, Prasanga Samarasinghe +2
The study of spatial audio and room acoustics aims to create immersive audio experiences by modeling the physics and psychoacoustics of how sound behaves in space. In the long hist…