Intelligent Detection Model Based on a Fully Convolutional Neural Network for Pavement Cracks
Duo Ma1, 2, 3, Hongyuan Fang1, 2, 3, *, Binghan Xue1, 2, 3, Fuming Wang1, 2, 3, Mohammed A. Msekh4, Chiu Ling Chan5
CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 1267-1291, 2020, DOI:10.32604/cmes.2020.09122
- 28 May 2020
(This article belongs to the Special Issue: Machine Learning based Methods for Mechanics)
Abstract The crack is a common pavement failure problem. A lack of periodic
maintenance will result in extending the cracks and damage the pavement, which will
affect the normal use of the road. Therefore, it is significant to establish an efficient
intelligent identification model for pavement cracks. The neural network is a method of
simulating animal nervous systems using gradient descent to predict results by learning a
weight matrix. It has been widely used in geotechnical engineering, computer vision,
medicine, and other fields. However, there are three major problems in the application of
neural networks to… More >