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Ziqi Fan

2 accepted papers

2021

Prediction of Object Geometry from Acoustic Scattering Using Convolutional Neural Networks

ICASSP 2021accepted

Acoustic scattering is strongly influenced by boundary geometry of objects over which sound scatters. The present work proposes a method to infer object geometry from scattering features by training convolutional neural networks. The training data is generated from a fast numerical solver developed…

Cited by 0SourceScholar
2020

Fast Acoustic Scattering Using Convolutional Neural Networks

ICASSP 2020accepted

Diffracted scattering and occlusion are important acoustic effects in interactive auralization and noise control applications, typically requiring expensive numerical simulation. We propose training a convolutional neural network to map from a convex scatterer's cross-section to a 2D slice of the re…

Cited by 0SourceScholar