High-Accuracy Insulator Defect Detection for Overhead Transmission Lines Based on Improved YOLOv5
As a key component in overhead cables, insulators play an important role. However, in the process of insulator inspection, due to background interference, small fault area, limitations of manual detection, and other factors, detection is difficult, has low accuracy, and is prone to missed detection...
Main Authors: | Yourui Huang, Lingya Jiang, Tao Han, Shanyong Xu, Yuwen Liu, Jiahao Fu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-12-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/12/24/12682 |
Similar Items
-
Insulator detection and damage identification based on improved lightweight YOLOv4 network
by: Gujing Han, et al.
Published: (2021-11-01) -
Online insulator defects detection and application based on YOLOv7-tiny algorithm
by: Sheng Wu, et al.
Published: (2024-03-01) -
Research on Edge Detection Model of Insulators and Defects Based on Improved YOLOv4-tiny
by: Boqiang Li, et al.
Published: (2023-01-01) -
Research on Insulator Defect Detection Based on an Improved MobilenetV1-YOLOv4
by: Shanyong Xu, et al.
Published: (2022-11-01) -
A lightweight insulator defect detection algorithm based on the improved YOLOv5
by: JI Shichao, et al.
Published: (2023-12-01)