Dec 5, 2023 · This review presents a comprehensive analysis of machine vision-based PCB defect detection algorithms, traversing the realms of machine learning and deep learning.

Mar 28, 2024 · Existing deep learning-based PCB defect detection methods are difficult to simultaneously achieve the goals of high detection accuracy, fast detection speed, and small …

This PCB defect detection system uses PyTorch and a Kaggle dataset to identify defects in printed circuit boards. It employs advanced computer vision techniques with preprocessing, …

Nov 1, 2024 · This paper proposes a printed circuit board (PCB) defect detection algorithm based on deep learning, which can improve product quality and avoid potential failures and accidents …

Jul 22, 2024 · Improving the accuracy and generalization of PCB defect detection models remains a significant challenge. This paper proposes a high-precision, robust, and real-time end-to-end …

detection of PCB defects is crucial as it directly impacts product quality and reliability. The primary challenges in PCB defect detection include missed detections and false alarms, particularly …

Jul 22, 2024 · This work categorized PCB surface defects into 9 distinct categories based on factors such as their causes, locations, and morphologies and developed a dataset of PCB …

This project focuses on automatic defect detection in Printed Circuit Boards (PCBs) using YOLOv8, a state-of-the-art object detection model. By leveraging the DeepPCB dataset, the …

Mar 6, 2023 · PCB defect detection not only helps to improve the yield of circuit board production, but also reduces repair costs caused by defects . According to the detection method, PCB …

May 7, 2021 · In order to ensure high yield and save labor cost, this paper applied two kinds of target detection network to PCB defect detection and classification tasks. Experiments show …