Abstract
This study explores an automated method for identifying cracks on a concrete bridge structure using an unmanned aerial vehicle (UAV) equipped with a high-resolution camera. First, images are captured from the bridge, then a novel automated algorithm are used to isolate the region of interest. The deep learning algorithm then detects cracks on the structure using a pre-trained Convolutional Neural Network (CNN) model. The proposed method was tested on Tran Phu bridge, and the results confirmed the effectiveness of the UAV-based inspections for identifying cracks on structures.
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