About this document
YOLOv10 for PCB Defect Detection by Jorge Barabaddas is a document available to read on EtoBox.
This study presents a deep learning-based system using YOLOv10 for detecting defects in Printed Circuit Boards (PCBs), addressing inefficiencies in traditional inspection methods. YOLOv10 incorporates architectural advancements that enhance feature extraction and localization accuracy, achieving high precision (96%) and recall (97%) with a custom dataset of 1,260 PCB samples. The model
- Author
- Jorge Barabaddas
- Language
- EN