Improvement of Lightweight Convolutional Neural Network Model Based on YOLO Algorithm and Its Research in Pavement Defect Detection

To ensure the safe operation of highway traffic lines, given the imperfect feature extraction of existing road pit defect detection models and the practicability of detection equipment, this paper proposes a lightweight target detection algorithm with enhanced feature extraction based on the YOLO (Y...

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Bibliographic Details
Main Authors:	Du, F.-J (Author), Jiao, S.-J (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	automated inspection Automated inspection Convolution convolutional neural network Convolutional neural network Convolutional neural networks deep learning Deep learning Defect detection Defects embedded equipment Embedded equipments Extraction Feature extraction Features extraction Model-based OPC Motor transportation Neural network model Pavement defect pavement defects Pavements Statistical tests YOLOv5S
Online Access:	View Fulltext in Publisher

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View Fulltext in Publisher

Improvement of Lightweight Convolutional Neural Network Model Based on YOLO Algorithm and Its Research in Pavement Defect Detection

Internet

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