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Physics-based reward driven image analysis in microscopy
April 23, 2024, 4:43 a.m. | Kamyar Barakati, Hui Yuan, Amit Goyal, Sergei V. Kalinin
cs.LG updates on arXiv.org arxiv.org
Abstract: The rise of electron microscopy has expanded our ability to acquire nanometer and atomically resolved images of complex materials. The resulting vast datasets are typically analyzed by human operators, an intrinsically challenging process due to the multiple possible analysis steps and the corresponding need to build and optimize complex analysis workflows. We present a methodology based on the concept of a Reward Function coupled with Bayesian Optimization, to optimize image analysis workflows dynamically. The Reward …
abstract analysis arxiv build cond-mat.mtrl-sci cs.lg datasets electron human image images materials microscopy multiple operators physics process type vast
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