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</html><description>This project is an application of neural techniques to synthetic-wave interferometry. It aims to improve on the methods of Swept-Angle Synthetic Wave Interferometry (Kotwal et al. 2022) by replacing the current depth recovery pipeline with one that is capable of adapting to correlated sources of noise and measurement imperfections by learning a more robust phase &hellip; Continue reading ""</description><thumbnail_url>https://mscvprojects.ri.cmu.edu/f23team12/wp-content/uploads/sites/89/2023/05/lagrida_latex_editor.png</thumbnail_url></oembed>

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