Enhancing the robustness of solar photovoltaic fault classification based on depthwise separable group equivariant CNNs

Enhancing the robustness of solar photovoltaic fault classification based on depthwise separable group equivariant CNNs

Solar photovoltaic (PV) power generation has experienced significant growth and thermal infrared (IR) imaging via unmanned aerial vehicles (UAVs) has become an efficient method for inspecting large-scale PV plants. However, variations in UAV flight paths and weather conditions cause orientation chan...

Full description

Saved in:
Bibliographic Details
Main Authors: Jielong Guo, Chak Fong Chong, Pedro Henriques Abreu, Chao Mao, Chan-Tong Lam, Benjamin K. Ng
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Alexandria Engineering Journal
Subjects:
Group equivariant convolution
Depthwise separable convolution
Solar photovoltaic module
Fault classification
Robustness
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016825005599
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.sciencedirect.com/science/article/pii/S1110016825005599

Similar Items