Using computer vision and neural networks for defect detection in manufacturing - Sotnychenko, Viktor (National Technical University "Kharkiv Polytechnic Institute", 2025)
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.
Keywords: computer vision; neural networks; defect detection; deep learning; automation; manufacturing quality control