Automatic Defect Detection in Wind Turbine Blade Images: Model Benchmarks and Re-Annotations-Reference-Cited by-同舟云学术

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Automatic Defect Detection in Wind Turbine Blade Images: Model Benchmarks and Re-Annotations

Published:2023-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)
language:
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Author:

Gohar Imad¹,See John²,Halimi Abderrahim³,Yew Weng Kean¹

Affiliation:

1. School of Engineering and Physical Sciences, Heriot-Watt University,Putrajaya,Malaysia

2. School of Mathematical and Computer Sciences, Heriot-Watt University,Putrajaya,Malaysia

3. School of Engineering and Physical Sciences, Heriot-Watt University,Edinburgh,United Kingdom

Funder

UK Royal Academy of Engineering

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10221939/10221894/10223074.pdf?arnumber=10223074

Reference22 articles.

1. Online dynamic reliability evaluation of wind turbines based on drone-assisted monitoring;kabir;ArXiv Preprint,2022

2. Wind Turbine Surface Damage Detection by Deep Learning Aided Drone Inspection Analysis

3. Identification of surface defects on solar pv panels and wind turbine blades using attention based deep learning model;dwivedi;ArXiv Preprint,2022

4. Portable motorized telescope system for wind turbine blades damage detection

5. End-to-End Object Detection with Transformers

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