FPCNet: Fast Pavement Crack Detection Network Based on Encoder-Decoder Architecture

4 July 2019

Papers citing "FPCNet: Fast Pavement Crack Detection Network Based on Encoder-Decoder Architecture"

7 / 7 papers shown

Title
Deep Learning for Segmentation of Cracks in High-Resolution Images of Steel Bridges Andrii Kompanets Gautam Pai R. Duits Davide Leonetti Bert Snijder 73 1 0 26 Mar 2024
NHA12D: A New Pavement Crack Dataset and a Comparison Study Of Crack Detection Algorithms Zhening Huang Weiwei Chen A. Al-Tabbaa I. Brilakis 26 12 0 02 May 2022
Evaluation and Comparison of Deep Learning Methods for Pavement Crack Identification with Visual Images Kai Lu 19 1 0 20 Dec 2021
Rethinking Lightweight Convolutional Neural Networks for Efficient and High-quality Pavement Crack Detection Kai Li Jie Yang Siwei Ma Bo Wang Shanshe Wang Ying-fang Tian Zhiquan Qi 78 12 0 13 Sep 2021
Advances in deep learning methods for pavement surface crack detection and identification with visible light visual images Kai-Di Lu 45 6 0 29 Dec 2020
Deep Learning Frameworks for Pavement Distress Classification: A Comparative Analysis Vishal Mandal Abdul Rashid Mussah Y. Adu-Gyamfi 48 53 0 21 Oct 2020
Optimized Deep Encoder-Decoder Methods for Crack Segmentation Jacob König M. Jenkins M. Mannion P. Barrie Gordon Morison 57 82 0 14 Aug 2020