Weather-Adaptive Synthetic Data Generation for Enhanced Power Line Inspection Using StarGAN

Accurately detecting power line defects under diverse weather conditions is crucial for ensuring power grid reliability and safety. Existing power line inspection datasets, while valuable, often lack the diversity needed for training robust machine learning models, particularly for adverse weather s...

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Bibliographic Details
Main Authors: Blessing Agyei Kyem, Joshua Kofi Asamoah, Ying Huang, Armstrong Aboah
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10807178/
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