Deep Learning-Based Road Pavement Inspection by Integrating Visual Information and IMU

This study proposes a deep learning method for pavement defect detection, focusing on identifying potholes and cracks. A dataset comprising 10,828 images is collected, with 8662 allocated for training, 1083 for validation, and 1083 for testing. Vehicle attitude data are categorized based on three-ax...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Chen-Chiung Hsieh, Han-Wen Jia, Wei-Hsin Huang, Mei-Hua Hsih
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2024-04-01
Sarja:	Information
Aiheet:	image recognition deep learning pavement inspection intelligent inspection
Linkit:	https://www.mdpi.com/2078-2489/15/4/239
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