Crack-ConvT Net: A Convolutional Transformer Network for Crack Segmentation in Underwater Dams

Abstract Crack detection is a critical approach to ensuring the structural health of dams. However, challenges like uneven underwater lighting, sediment interference, and complex backgrounds often hinder traditional detection methods, leading to feature loss and false detections. To address these is...

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Bibliografski detalji

Glavni autori:	Pengfei Shi, Hongzhu Chen, Zaiming Geng, Xinnan Fan, Yuanxue Xin
Format:	Artigo
Jezik:	Inglês
Izdano:	Springer 2025-06-01
Serija:	Complex & Intelligent Systems
Teme:	Underwater dam Crack segmentation Skip connection Feature extraction Information aggregation
Online pristup:	https://doi.org/10.1007/s40747-025-01957-y
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