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Showing 1 to 2 of 2 for “"Defect segmentation"”.
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Strategies for the Characterization and Virtual Testing of SLM 316L Stainless Steel
… time consuming, traditionally requiring manual segmentation of imaged features. Two Python-based image analysis tools are developed here to automate the instance segmentation of manufacturing defects and subgranular cell features commonly found in SLM 316L stainless steel (SS) for quantitative …
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Deep learning models for defect and anomaly detection on industrial surfaces
… in computer vision and machine learning for defect detection, challenges persist, such as defect variability and the computational burden. This thesis presents specialized deep learning architectures addressing defect classification, segmentation, and detection in textiles, civil engineering, …