Automated Detection of Embankment Piping and Leakage Hazards Using UAV Visible Light Imagery: A Frequency-Enhanced Deep Learning Approach for Flood Risk Prevention

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Bibliographische Detailangaben
Veröffentlicht in:	Remote Sensing vol. 17, no. 21 (2025), p. 3602-3638
1. Verfasser:	Liu, Jian
Weitere Verfasser:	Wang, Zhonggen, Li, Renzhi, Zhao Ruxin, Zhang Qianlin
Veröffentlicht:	MDPI AG
Schlagworte:	Feature extraction Warning systems Datasets Early warning systems Infrastructure Convolution Flood control Edge computing Computer applications Machine learning Efficiency Background noise Remote sensing Fourier transforms Decision making Leakage Computational efficiency Emergency communications systems Risk management Algorithms Embankments Accuracy Flood management Deep learning Inspection Parameter sensitivity Safety Environmental conditions Environmental risk Public safety Monitoring Floating point arithmetic Floods Cost effectiveness Infrared imaging Safety management Unmanned aerial vehicles Frequency domain analysis Computing costs Design Light
Online-Zugang:	Citation/Abstract Full Text + Graphics Full Text - PDF
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