Image Enhanced Mask R-CNN: A Deep Learning Pipeline with New Evaluation Measures for Wind Turbine Blade Defect Detection and Classification

Demand for wind power has grown, and this has increased wind turbine blade (WTB) inspections and defect repairs. This paper empirically investigates the performance of state-of-the-art deep learning algorithms, namely, YOLOv3, YOLOv4, and Mask R-CNN for detecting and classifying defects by type. The...

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Detalles Bibliográficos
Autores principales: Zhang, Jiajun, Cosma, Georgina, Watkins, Jason
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321286/
https://www.ncbi.nlm.nih.gov/pubmed/34460702
http://dx.doi.org/10.3390/jimaging7030046

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321286/
https://www.ncbi.nlm.nih.gov/pubmed/34460702
http://dx.doi.org/10.3390/jimaging7030046

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