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

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: Fu-Jun Du, Shuang-Jian Jiao
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Sensors
Subjects:
pavement defects
deep learning
convolutional neural network
YOLOv5S
automated inspection
embedded equipment
Online Access:https://www.mdpi.com/1424-8220/22/9/3537

Internet

https://www.mdpi.com/1424-8220/22/9/3537

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