Autonomous concrete crack detection using deep fully convolutional neural network

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Automated Multi-Class Concrete Crack Detection and Severity Classification Using CNN-Based Deep Learning

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Asphalt Pavement Crack Detection Based on SegNet Network

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Non-Invasive Testing of Physical Systems Using Topological Sensitivity

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Detection of Cracks in Surfaces and Materials Using Convolutional Neural Network

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Classification of vein pattern recognition using hybrid deep learning

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Road and Bridge Expansion Joint Crack Detection and Disease Classification Based on Deep Learning and Morphology

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Tunnel Crack Detection and Evaluation Based on Improved Holistically Nested Edge Detection Network

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AI-Enabled Unmanned Aerial System for Highway Bridge Claims Management

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Artificial Intelligence Tools in the Management of Reinforced Concrete Structures: Potential, Critical Issues, and Preliminary Results on Structural Degradation

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CrackNet++: An enhanced UNet architecture employing tri-axial fusion attention and multi-scale gated fusion for precise crack segmentation and quantification

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Deep learning-based detection and evaluation of pavement surface damage

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Crack Identification and Severity Analysis via Computer Vision: Comparative Study of RGB and Grayscale Imagery

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