Results 21 to 30 of about 9,669 (275)

Concrete Pavement Crack Detection Based on Dilated Convolution and Multi-features Fusion [PDF]

open access: yesJisuanji kexue, 2022
Crack detection for concrete pavement is an important fundamental task to ensure the safety of the road.Due to the complicated concrete pavement background and the diversity of cracks,a novel crack detection network of concrete pavement based on dilated ...
QU Zhong, CHEN Wen
doaj   +1 more source

Deep Domain Adaptation for Pavement Crack Detection

open access: yesIEEE Transactions on Intelligent Transportation Systems, 2022
Published on IEEE Transactions on Intelligent Transportation ...
Huijun Liu   +6 more
openaire   +2 more sources

Deep Learning based Pavement Crack Detection System

open access: yesJournal of Physics: Conference Series, 2023
Abstract The pavement crack causes the highway service life to shorten, the safety hidden danger to increase. The low efficiency and high cost of manual inspection makes it difficult to detect pavement cracks. This paper proposes a fast and efficient deep learning pavement crack detection system.
Lingjun Yu, Qi Li
openaire   +1 more source

Pavement crack analysis by referring to historical crack data based on multi-scale localization.

open access: yesPLoS ONE, 2020
Pavement crack analysis, which deals with crack detection and crack growth detection, is a crucial task for modern Pavement Management Systems (PMS). This paper proposed a novel approach that uses historical crack data as reference for automatic pavement
Xianglong Wang   +3 more
doaj   +1 more source

A framework for pavement crack detection and classification

open access: yesIOP Conference Series: Materials Science and Engineering, 2020
Abstract Pavement damage detection is indeed a very important process for the management of roads. Nowadays, scholars are focusing on finding a simple and accurate way to detect road cracks aiming to increase its life span and improve its safety and quality.
Ahed Habib, Kunt, Mehmet Metin
openaire   +1 more source

Automated Pavement Crack Damage Detection Using Deep Multiscale Convolutional Features

open access: yesJournal of Advanced Transportation, 2020
Road pavement cracks automated detection is one of the key factors to evaluate the road distress quality, and it is a difficult issue for the construction of intelligent maintenance systems.
Weidong Song   +4 more
doaj   +1 more source

Crack Detection of Concrete Pavement With Cross-Entropy Loss Function and Improved VGG16 Network Model

open access: yesIEEE Access, 2020
Concrete pavement defects are an important indicator reflecting the safety status of pavement. However, it is difficult to accurately detect the concrete pavement cracks due to the complex concrete pavement environment, such as uneven illumination ...
Zhong Qu   +3 more
doaj   +1 more source

STrans-YOLOX: Fusing Swin Transformer and YOLOX for Automatic Pavement Crack Detection

open access: yesApplied Sciences, 2023
Automatic pavement crack detection is crucial for reducing road maintenance costs and ensuring transportation safety. Although convolutional neural networks (CNNs) have been widely used in automatic pavement crack detection, they cannot adequately model ...
Hui Luo   +3 more
doaj   +1 more source

Tiled fuzzy Hough transform for crack detection [PDF]

open access: yes, 2015
Surface cracks can be the bellwether of the failure of any component under loading as it indicates the component's fracture due to stresses and usage. For this reason, crack detection is indispensable for the condition monitoring and quality control
Al-Habaibeh, A   +5 more
core   +1 more source

Pavement Crack Detection Using Convolutional Neural Network

open access: yesEPiC Series in Computing, 2020
Automating the process of detecting pavement cracks became a challenge mission. In the last few decades, many methods were proposed to solve this problem. The reason is that maintaining a stable condition of roads is essential for the safety of people and public properties.
Alaa Sheta   +3 more
openaire   +2 more sources

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