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Deep Learning for Defect Detection by vaibhavlonewolf is a document available to read on EtoBox.
This study presents a deep learning-based automatic defect detection model aimed at enhancing sustainable smart manufacturing, particularly for small-scale products. The model utilizes the YOLOv4 deep learning framework and OpenCV for real-time defect identification during the manufacturing process, demonstrated through its application in detecting liquefied gas volume defects in disposable gas lighters. By offering a low-cost solution suitable for SMEs, the proposed system aims to reduce labor costs and im
- Author
- vaibhavlonewolf
- Language
- EN