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Deep Learning Based Defect Detection Research on Printed Circuit Boards Cover

Deep Learning Based Defect Detection Research on Printed Circuit Boards

By: Qihang Yang and  Fan Yu  
Open Access
|Jul 2024

Figures & Tables

Figure 1.

Diagram of YOLOv8 structure
Diagram of YOLOv8 structure

Figure 2.

Schematic diagram of C2F module
Schematic diagram of C2F module

Figure 3.

Bottleneck Schematic Diagram
Bottleneck Schematic Diagram

Figure 4.

Schematic diagram of SPPF structure
Schematic diagram of SPPF structure

Figure 5.

Pcb defect detection effect
Pcb defect detection effect

Figure 6.

Loss, Precision, Recall, mPA0.5 and mAP0.5-0.95 curves
Loss, Precision, Recall, mPA0.5 and mAP0.5-0.95 curves

Experimental Results

ModelmAP(%)FPSQuantity of participants/M
Faster R-CNN89.520.5125.3
YOLOv585.379.442.7
YOLOv787.1102.537.2
YOLOv892.3157.228.5

Experimental Environment

Experimental environmentVersion
CPUIntel Core i7-11800H
GPUNVIDIA GeForce RTX307
LanguagePython3.7
Deep Learning FrameworkPytorch1.11.0
CUDA11.3.0
CompilerPycharm2021
Language: English
Page range: 51 - 58
Published on: Jul 21, 2024
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2024 Qihang Yang, Fan Yu, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.