Data set of insulator defect detection based on UAV by YOLO
收藏DataCite Commons2024-05-29 更新2025-04-16 收录
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https://ieee-dataport.org/documents/data-set-insulator-defect-detection-based-uav-yolo
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资源简介：
The dataset forwas collected by UAVs equipped with camera heads to capture images of insulators on power transmission lines. These images have a resolution of 3872×2592 pixels. A total of 488 insulator defect images were selected, and the data was annotated using the LabelMe annotation software. This study's dataset annotated four types of labels: insulator, damaged, Flashover, and hammer. The insulator is a positive class label, and damaged, Flashover, and hammer are negative class labels.
提供机构：
IEEE DataPort
创建时间：
2024-05-29
