Abstract
Image segmentation is a valuable tool for visual image data inspection of semiconductor device structures. For the large amounts of data provided by recent advancements in automated scanning electron microscope (SEM) and focused ion beam-scanning electron microscope (FIB-SEM) data acquisition, automatic segmentation becomes indispensable to fully exploit the information contained in the data in automated characterization workflows. Using two exemplary FIB-SEM tomography datasets, we explored artificial intelligence based image segmentation using only a minimum amount of training images annotated by a human user.
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2024
ASM International
Issue Section:
AI Applications for Failure Analysis
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