djene-mengistu/Machine-Vision-and-Anomaly-Detection-Papers
This repo contains state-of-the-art deep learning models for industrial anomaly detection, defect segmentation, detection, and classification, with other industrial machine vision applications.
This collection of resources helps quality control engineers and manufacturing operations managers implement automated inspection systems. It provides advanced deep learning models that take images of industrial products as input to identify, classify, and localize surface defects or anomalies. The goal is to improve efficiency and precision in production by catching defects early and enabling preventive maintenance.
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Use this if you need to set up or enhance an automated visual inspection system for manufactured goods to detect and categorize product defects.
Not ideal if your primary need is general machine vision tasks unrelated to industrial defect detection or if you are looking for ready-to-use software rather than research papers and associated code.
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Feb 19, 2025
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