Detection of sealed and unsealed cracks with complex backgrounds using deep convolutional neural network

Crack Deep Network (CrackDN) is proposed in this research with the purpose of detecting sealed and unsealed cracks with complex road backgrounds. CrackDN is based on Faster Region Convolutional Neural Network (Fast-RCNN) architecture by embedding a sensitivity detection network parallel to the feature extraction Convolutional Neural Network (CNN), both of which are then connected to the Region Proposal Refinement Network (RPRN) for …