Quantitative Assessment Framework for Non-Structural Bird’s Nest Risk Information of Transmission Tower in High-Resolution UAV Panoramic Images

Author:

Liao Jiawei1,Xu Haitao1,Fang Xia1,Zhang Dingcheng1,Zhu Gaoyi1

Affiliation:

1. Sichuan University,School of Mechanical Engineering,Chengdu,China

Funder

National Natural Science Foundation of China

Research and Development

Publisher

IEEE

Reference13 articles.

1. Deep High-Resolution Representation Learning for Visual Recognition

2. Deep residual learning for image recognition;kaiming;Proc 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016

3. Simple baselines for human pose estimation and tracking;xiao;Proc Proceedings of the European Conference on Computer Vision (ECCV),2018

4. Faster RCNN: towards real-time object detection with region proposal networks;ren;Proc Adv Neural Inf Process Syst Montreal,2015

5. Study on nest material flashover risk level assessment of AC overhead transmission line;shenghui;Proc 2021 IEEE Electrical Insulation Conference (EIC),2021

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