3.8 Proceedings Paper

Development of an automatic detector of cracks in concrete using machine learning

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.proeng.2017.01.418

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machine learning; deep learning; cracked concrete; automatic detection

资金

  1. Grants-in-Aid for Scientific Research [15H04028] Funding Source: KAKEN

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This study is to develop a detector that automatically detects cracks from the photographs of concrete structures, using convolution neural network which is a kind of deep learning. Firstly, photographs of concrete were collected for the learning data. Secondly, pictures of cracked part, chalk letter part, joint part, surface part and others part were produced from these photographs for the dataset. Thirdly, classifier to classify into these 5 class from pictures was created using the dataset and convolution neural network. Finally, the automatic detector was produced using this classifier. (C) 2017 The Authors. Published by Elsevier Ltd.

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