Hierarchical Convolutional Neural Network with Feature Preservation and Autotuned Thresholding for Crack Detection

Drone imagery is increasingly used in automated inspection for infrastructure surface defects, especially in hazardous or unreachable environments. In machine vision, the key to crack detection rests with robust and accurate algorithms for image processing. To this end, this paper proposes a deep le...

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Bibliographic Details
Published in:	arXiv.org
Main Authors:	Zhu, Qiuchen, Tran, Hiep Dinh, Manh Duong Phung, Ha, Quang Phuc
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 21.04.2021
Subjects:	Algorithms Artificial neural networks Bridge inspection Datasets Feature extraction Feature maps Hazardous areas Image processing Machine learning Machine vision Monorails Neural networks Occultation Post-production processing Surface cracks Surface defects Unmanned aerial vehicles
ISSN:	2331-8422
Online Access:	Get full text
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