Research on Defect Detection Method of Railway Transmission Line Insulators Based on GC-YOLO

The insulator defect targets in Unmanned Aerial Vehicle (UAV) images are often small and set against complex backgrounds. Consequently, traditional object detection algorithms commonly struggle to identify these minor defects. To enhance precision and recall in detecting insulator defects, a novel m...

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Veröffentlicht in:	IEEE access 2023, Vol.11, p.102635-102642
Hauptverfasser:	Ding, Lu, Rao, Zhi Qiang, Ding, Biao, Li, Shao Jia
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms CFPNet Computational modeling Computer networks Convolution Convolutional neural networks Defects EVCBlock Feature extraction Feature maps GC-YOLO ghost convolution Ghosts insulator-defect detection Insulators Modules Object detection Object recognition Power transmission lines Rail transportation Recall Redundancy Transmission lines Unmanned aerial vehicles
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