270 / 2021-11-08 12:04:25
Semantic Segmentation and Defect Detection of Aerial Insulators of Transmission Lines
Power inspection,insulator,semantic segmentation,target detection,defect detection
Draft Rejected
Zhangpeng Zhou / Maintenance company of State Grid Power Company in Gansu Province
Shengli Wang / Maintenance company of State Grid Power Company in Gansu Province
Wen bin Zhao / shanghai university of electric power
Aiming at the problems of low accuracy and poor generalization ability of insulator defect detection in complex aerial images by existing insulator defect detection algorithms, the possibility of using semantic segmentation technology to simplify insulator features in complex images is explored. The semantic segmentation model DeepLabv3 is cascaded with the target detector yolov3 to realize the semantic segmentation of insulators in aerial images and the detection of defects. The experimental results show that the use of the strategy of semantic segmentation and target detection can increase the accuracy of insulator defect detection by 12.58%, which effectively improves the performance of the detection model.

 
Important Date
  • Conference Date

    Jul 11

    2023

    to

    Aug 18

    2023

  • Nov 10 2021

    Draft paper submission deadline

  • Dec 10 2021

    Registration deadline

  • Dec 11 2021

    Contribution Submission Deadline

Sponsored By
IEEE IAS
Organized By
IEEE IAS Student Chapter of Southwest Jiaotong University (SWJTU)
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
IEEE PELS (Power Electronics Society) Student Chapter of HUST