Lightweight defect detection algorithm of tunnel lining based on knowledge distillation

Due to the influence of construction quality, engineering geology and hydrological environment, defects such as dehollowing and insufficient compaction can occur in tunnels. Aiming at the problems of complex detection model, poor real-time performance and low accuracy of the current tunnel lining de...

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Veröffentlicht in:	Scientific reports Jg. 14; H. 1; S. 27178 - 16
Hauptverfasser:	Zhu, Anfu, Xie, Jiaxiao, Wang, Bin, Guo, Heng, Guo, Zilong, Wang, Jie, Xu, Lei, Zhu, SiXin, Yang, Zhanping
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 08.11.2024 Nature Publishing Group Nature Portfolio
Schlagworte:	639/166/986 639/166/987 Accuracy Algorithms Deep learning Distillation Engineering geology Geology Humanities and Social Sciences Knowledge distillation Model compression algorithms multidisciplinary Science Science (multidisciplinary) Tunnel detection Tunnel linings Deep learning Tunnel detection Knowledge distillation Model compression algorithms
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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