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

• Datum: 2025
• Hauptverfasser: Верлань , А.А., Фастовець , Є.Р.
• Format: Artikel
• Sprache: Englisch
• Veröffentlicht: Інститут проблем реєстрації інформації НАН України 2025
• Schlagworte: quality control; defect detection; neural networks; artificial intelligence; printed circuit boards; YOLO; optical inspection
• Online Zugang: 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...