Improved YOLOV5-Based UAV Pavement Crack Detection-Reference-Cited by-同舟云学术

Improved YOLOV5-Based UAV Pavement Crack Detection

Published:2023-07-15 Issue:14 Volume:23 Page:15901-15909
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Xing Jian¹^ORCID,Liu Ying²^ORCID,Zhang Guang-Zhu³

Affiliation:

1. Computer and Control Engineering, Northeast Forestry University, Harbin, China

2. College of Computer and Control Engineering, Northeast Forestry University, Harbin, China

3. College of Civil Engineering and Transportation, Northeast Forestry University, Harbin, China

Funder

Research Project of the Heilongjiang Province Transportation Department through the Intelligent Monitoring Application of UAV in the Process of Highway Construction

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10183770/10144553.pdf?arnumber=10144553

Reference49 articles.

1. Image‐based concrete crack assessment using mask and region‐based convolutional neural network

2. Real-time multiple damage mapping using autonomous UAV and deep faster region-based neural networks for GPS-denied structures

3. Autonomous concrete crack detection using deep fully convolutional neural network

4. NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion

5. Autonomous UAVs for Structural Health Monitoring Using Deep Learning and an Ultrasonic Beacon System with Geo-Tagging

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