This paper concerns the development of a machine learning tool to detect anomalies in the molecular structure of Gallium Arsenide. We employ a combination of a CNN and a PCA reconstruction to create the model. using real images taken with an electron microscope in training and testing. The methodology developed allows for the creation of a defect detection model. https://fitnessgravesyardes.shop/product-category/plastic-idler-pulley/
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