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2024-09-01

Latent Diffusion Models to Enhance the Performance of Visual Defect Segmentation Networks in Steel Surface Inspection

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Sensors

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A Fast Deep Learning Based Approach for Unsupervised Anomaly Detection in 3D Data

Sergio Presa Feijoo

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Containerized edge architecture for manufacturing data analysis in Cyber-Physical Production Systems

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Photometric Stereo-Based Defect Detection System for Steel Components Manufacturing Using a Deep Segmentation Network

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Sensors

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An Inspection and Classification System for Automotive Component Remanufacturing Industry Based on Ensemble Learning

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Information

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Synthetic Data Set Generation for the Evaluation of Image Acquisition Strategies Applied to Deep Learning Based Industrial Component Inspection Systems

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