Multimodal geometric AutoEncoder (MGAE) for rail fasteners tightness evaluation with point clouds & monocular depth fusion

•Introduces a Multimodal Geometric AutoEncoder (MGAE) for rail fastener tightness evaluation.•Integrates point cloud and monocular depth fusion for improved feature extraction.•Reduces manual annotation efforts and increases computational efficiency in rail inspection.•Provides a scalable, automated...

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Veröffentlicht in:	Measurement : journal of the International Measurement Confederation Jg. 244; S. 116557
Hauptverfasser:	Qiu, Shi, Zaheer, Qasim, Muhammad Ahmed Hassan Shah, S., Faizan Hussain Shah, Syed, Ehsan, Haleema, Atta, Zunaira, Ai, Chengbo, Wang, Jin, Wang, Weidong, Peng, Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 28.02.2025
Schlagworte:	Autoencoder Fastener tightness Multimodal approach Rail fasteners Rail infrastructure Rail infrastructure Multimodal approach Autoencoder Rail fasteners Fastener tightness
ISSN:	0263-2241
Online-Zugang:	Volltext
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