Using computer vision and neural networks for defect detection in manufacturing

Abstract

The research explores the application of computer vision and neural networks for automated defect detection in manufacturing processes. Deep learning-based algorithms analyze visual data to identify defects, optimize quality control, and enhance production efficiency [1]. The study aims to reduce human error, increase detection accuracy, and minimize production losses.