Abstract:Atomic force microscopy (AFM) is routinely used as a metrological tool among diverse scientific and engineering disciplines. A typical AFM, however, is intrinsically limited by low throughput and is inoperable under extreme conditions. Thus, this work attempts to provide an alternative to a conventional optical microscope (OM) by training a deep learning model to predict surface topography from surface OM images. The feasibility of this novel methodology is shown with germanium‐on‐nothing (GON) samples, which … Show more
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