CrackCLF: Automatic Pavement Crack Detection Based on Closed-Loop Feedback

Automatic pavement crack detection is an important task to ensure the functional performances of pavements during their service life. Inspired by deep learning (DL), the encoder-decoder framework is a powerful tool for crack detection. However, these models are usually open-loop (OL) systems that te...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems 2024-06, Vol.25 (6), p.5965-5980
Hauptverfasser:	Li, Chong, Fan, Zhun, Chen, Ying, Lin, Huibiao, Moretti, Laura, Loprencipe, Giuseppe, Sheng, Weihua, Wang, Kelvin C. P.
Format:	Artikel
Sprache:	eng
Schlagworte:	Automatic pavement crack detection Closed loops closed-loop feedback Cracks Decoding Deep learning Defect detection encoder-decoder Encoders-Decoders Errors Feature extraction Feedback Flaw detection generative adversarial network Generative adversarial networks Image segmentation Machine learning Neural networks Pavements Road safety Roads Service life Surface cracks Training
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