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Applied Math Seminar | Xu Yang, Seismic tomography, image segmentation and deep learningExport this event to calendar

Thursday, March 5, 2020 — 11:30 AM EST

MC 5501<--break->


<--break->Speaker

 Xu Yang | Department of Mathematics, UC Santa Barbara

Title

Seismic tomography, image segmentation and deep learning

Abstract

Seismic tomography is a scientific field using realistic earthquake data to analyze the inner structure of our Earth. In this talk, we present a natural connection of three-dimensional seismic tomography to image segmentation problems, which we solve efficiently using deep neural networks with a UNet architecture. It is challenging to obtain sufficient valid data to train neural networks, and we overcome it by developing a fast synthetic data generator using multi-scale asymptotic analysis. The accuracy and parallelizability of the proposed algorithm is illustrated by comparing to the spectral element method. Moreover, the developed multi-scale algorithm can be also used to accelerate various standard applications in seismic tomography, including seismic traveltime tomography and full waveform inversion. 

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