September 10, 2025Remote SensingOpen Access

Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks

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The developed framework achieves a precision of 0.949 and an IoU of 87.92%, outperforming traditional models.
Experimental results highlight the framework's robust performance across various noise levels while processing UAV images.
The model integrates enhancements like Lightweight Feature Pyramid Attention and Edge Attention for improved pixel-level detection.
Real-time inference speed of 56.31 FPS establishes its practical application in automated infrastructure assessments.

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Implication

This analysis demonstrates advanced damage detection using UAV imagery in hydraulic structures, suggesting deep learning can improve inspection accuracy.

Cite This Study

Han et al. (2025) studied this question.

synapsesocial.com/papers/68c2404eb210217d6479a3b0 https://doi.org/10.3390/rs17152668

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Implication

This analysis demonstrates advanced damage detection using UAV imagery in hydraulic structures, suggesting deep learning can improve inspection accuracy.

Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks

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Discussion

Implication

Cite This Study

Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks

Key Points

Discussion

Implication

Cite This Study

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