Precise Detection for Dense PCB Components Based on Modified YOLOv8

• Published in: IEEE access Vol. 11; p. 1
• Main Authors: Ling, Qin, Isa, Nor Ashidi Mat, Asaari, Mohd Shahrimie Mohd
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Circuit boards; Computational modeling; Convolution; Costs; Feature extraction; Frames per second; Ghost convolution; High-precision; Image processing; Inspection; Lightweight; Machine learning algorithms; Optimization; PCB component detection; Precision engineering; Printed circuits; Sig-IoU loss

Effective detection of dense printed circuit board (PCB) components contributes to the optimization of automatic flow of production. In addition, PCB component recognition is also the essential prerequisite for early defect detection. Current PCB component detection approaches are not adept in both...