Insulator Faults Detection in Aerial Images from High-Voltage Transmission Lines Based on Deep Learning Model
Insulator fault detection is one of the essential tasks for high-voltage transmission lines’ intelligent inspection. In this study, a modified model based on You Only Look Once (YOLO) is proposed for detecting insulator faults in aerial images with a complex background. Firstly, aerial images with o...
Main Authors: | Chuanyang Liu, Yiquan Wu, Jingjing Liu, Zuo Sun, Huajie Xu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-05-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/11/10/4647 |
Similar Items
-
An Improved Method Based on Deep Learning for Insulator Fault Detection in Diverse Aerial Images
by: Jingjing Liu, et al.
Published: (2021-07-01) -
A Method of Insulator Faults Detection in Aerial Images for High-Voltage Transmission Lines Inspection
by: Jiaming Han, et al.
Published: (2019-05-01) -
MTI-YOLO: A Light-Weight and Real-Time Deep Neural Network for Insulator Detection in Complex Aerial Images
by: Chuanyang Liu, et al.
Published: (2021-03-01) -
Uncertainty-aware accurate insulator fault detection based on an improved YOLOX model
by: Zhiyong Dai
Published: (2022-11-01) -
Search Like an Eagle: A Cascaded Model for Insulator Missing Faults Detection in Aerial Images
by: Jiaming Han, et al.
Published: (2020-02-01)