Overview and comparison of neural network models for diagnostics and quality control in the production of printed circuit boards

• Дата: 2025
• Автори: Верлань , А.А., Фастовець , Є.Р.
• Формат: Стаття
• Мова: Англійська
• Опубліковано: Інститут проблем реєстрації інформації НАН України 2025
• Теми: quality control; defect detection; neural networks; artificial intelligence; printed circuit boards; YOLO; optical inspection
• Онлайн доступ: https://drsp.ipri.kiev.ua/article/view/336051
• Назва журналу: Data Recording, Storage & Processing

The article reviews and analyzes modern solutions based on neural networks for diagnostics and quality control of printed circuit boards (PCB). Various convolutional neural network (CNN) models, including LeNet-5, AlexNet, VGGNet, ResNet, and others, are reviewed, and their advantages and disadvanta...