A modified-yolov5s model for defect detection of printed circuit board
Author:
Affiliation:
1. Heilongjiang University,College of Electronic Engineering,Harbin,China,150080
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10054511/10054645/10055693.pdf?arnumber=10055693
Reference25 articles.
1. YOLO9000: Better, Faster, Stronger
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4. You Only Look Once: Unified, Real-Time Object Detection;redmon;2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016
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2. PCB Defect Detection Based on Improved Deep Learning Model;International Journal of Pattern Recognition and Artificial Intelligence;2024-08-09
3. Implementation of YOLOv8 Algorithm on Raspberry Pi for Automated PCB Quality Inspection;2024 International Electronics Symposium (IES);2024-08-06
4. Improved YOLOv5s combining enhanced backbone network and optimized self-attention for PCB defect detection;The Journal of Supercomputing;2024-05-25
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