• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
成果搜索

author:

Jiang, N. (Jiang, N..) [1] | Fan, J. (Fan, J..) [2]

Indexed by:

Scopus

Abstract:

The technical foundation of intelligent inspection of power lines is the detection of components in aerial images. With the rapid development of deep learning, new object detection technologies are constantly emerging. However, accurate annotation of data sets is equally crucial for improving detection performance. This study proposes a truth inference algorithm for transmission line components to improve the accuracy and reliability of annotated data. Propose Multi component label removal algorithm and Large box label removal algorithm for both normal sized and small-sized components, respectively. The experimental results show that our method has achieved significant results in improving the quality and accuracy of annotated data. This study is of great significance for improving the accuracy of annotation on power line datasets. © 2024 IEEE.

Keyword:

crowdsourcing ground truth inference object detection power line inspection

Community:

  • [ 1 ] [Jiang N.]Fuzhou University, School of Electrical Engineering and Automation, Fuzhou, China
  • [ 2 ] [Fan J.]Fuzhou University, School of Electrical Engineering and Automation, Fuzhou, China

Reprint 's Address:

Email:

Show more details

Related Keywords:

Source :

Year: 2024

Page: 222-226

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

Affiliated Colleges:

Online/Total:67/9996555
Address:FZU Library(No.2 Xuyuan Road, Fuzhou, Fujian, PRC Post Code:350116) Contact Us:0591-22865326
Copyright:FZU Library Technical Support:Beijing Aegean Software Co., Ltd. 闽ICP备05005463号-1