Autonomous concrete crack detection using deep fully convolutional neural network
Cited by (1,001)
Items 101–200 of 1,001
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- Automated pixel-level crack detection and quantification using deep convolutional neural networks for structural condition assessmentJingyue Yuan, Qiubing Ren, Chao Jia, Juntao Zhang, Jiake Fu, Mingchao Li · 2023 · Structures
- Enhancing pixel-level crack segmentation with visual mamba and convolutional networksChengjia Han, Handuo Yang, Yaowen Yang · 2024 · Automation in Construction
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- Automated crack pattern recognition from images for condition assessment of concrete structuresYiqing Liu, Justin K. W. Yeoh · 2021 · Automation in Construction
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- Bibliometric Analysis and Review of Deep Learning-Based Crack Detection Literature Published between 2010 and 2022Luqman Ali, Fady Alnajjar, Wasif Khan, Mohamed Adel Serhani, Hamad Al Jassmi · 2022 · Buildings
- Automated Surface Crack Detection in Historical Constructions with Various Materials Using Deep Learning-Based YOLO NetworkNarges Karimi, Mayank Mishra, Paulo Barbosa Lourenço · 2024 · International Journal of Architectural Heritage
- Real-time monitoring of concrete crack based on deep learning algorithms and image processing techniquesGang Xu, Qingrui Yue, Xiaogang Liu · 2023 · Advanced Engineering Informatics
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- In-situ concrete slump test incorporating deep learning and stereo visionNguyen Manh Tuan, Quach Van Hau, Sangyoon Chin, Seunghee Park · 2020 · Automation in Construction
- Automatic damage detection using anchor-free method and unmanned surface vesselZhili He, Shang Jiang, Jian Zhang, Gang Wu · 2021 · Automation in Construction
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- Damage detection using in-domain and cross-domain transfer learningZaharah Allah Bukhsh, Nils Jansen, Aaqib Saeed · 2021 · Neural Computing and Applications
- Automatic Pixel-Level Crack Detection for Civil Infrastructure Using Unet++ and Deep Transfer LearningQiaoning Yang, Xiaodong Ji · 2021 · IEEE Sensors Journal
- Automatic Rail Surface Defects Inspection Based on Mask R-CNNFeng Guo, Yu Qian, Dimitris C. Rizos, Zhi Suo, Xiaobin Chen · 2021 · Transportation Research Record Journal of the Transportation Research Board
- Region-Based CNN Method with Deformable Modules for Visually Classifying Concrete CracksLu Deng, Hong-Hu Chu, Peng Shi, Wei Wang, Xuan Kong · 2020 · Applied Sciences
- MultiDefectNet: Multi-Class Defect Detection of Building Façade Based on Deep Convolutional Neural NetworkKisu Lee, Goopyo Hong, Lee Sael, Sanghyo Lee, Ha Young Kim · 2020 · Sustainability
- Crack segmentation through deep convolutional neural networks and heterogeneous image fusionShanglian Zhou, Wei Song · 2021 · Automation in Construction
- Automatic Pixel-Level Pavement Crack Recognition Using a Deep Feature Aggregation Segmentation Network with a scSE Attention Mechanism ModuleWenting Qiao, Qiangwei Liu, Xiaoguang Wu, Biao Ma, Gang Li · 2021 · Sensors
- A hybrid attention deep learning network for refined segmentation of cracks from shield tunnel lining imagesShuai Zhao, Guokai Zhang, Dongming Zhang, Dao‐Yuan Tan, Hongwei Huang · 2023 · Journal of Rock Mechanics and Geotechnical Engineering
- Advancements and emerging trends in integrating machine learning and deep learning for SHM in mechanical and civil engineering: a comprehensive reviewAbdelwahhab Khatir, Roberto Capozucca, Samir Khatir, Erica Magagnini, Cuong Le Thanh, Mohamed Kamel Riahi · 2025 · Journal of the Brazilian Society of Mechanical Sciences and Engineering
- Autonomous Crack and Bughole Detection for Concrete Surface Image Based on Deep LearningYujia Sun, Yang Yang, Gang Yao, Fujia Wei, Mingpu Wong · 2021 · IEEE Access
- Structural engineering from an inverse problems perspectiveAdrien Gallet, Sam E. Rigby, Tyler N. Tallman, Xiangxiong Kong, Iman Hajirasouliha, A. Liew, Dong Liu, Liang Chen, Andreas Hauptmann, Danny Smyl · 2022 · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
- Tuning of data augmentation hyperparameters in deep learning to building construction image classification with small datasetsAndré Luiz Carvalho Ottoni, Raphael Melo de Amorim, Marcela S. Novo, Dayana Bastos Costa · 2022 · International Journal of Machine Learning and Cybernetics
- Autonomous detection of concrete damage under fire conditionsA. Diana Andrushia, N. Anand, T. Mary Neebha, Mohannad Zeyad Naser, Éva Lublóy · 2022 · Automation in Construction
- Deep Learning for Concrete Crack Detection and MeasurementMthabisi Adriano Nyathi, Jiping Bai, Ian David Wilson · 2024 · Metrology
- Detecting and localising damage based on image recognition and structure from motion, and reflecting it in a 3D bridge modelTatsuro Yamane, Pang‐jo Chun, Riki Honda · 2022 · Structure and Infrastructure Engineering
- Computer Vision-Based Statistical Crack Quantification for Concrete Structure MaintenanceHyunjin Bae, Yun‐Kyu An · 2022 · Measurement
- Advancing Bridge Structural Health Monitoring: Insights into Knowledge-Driven and Data-Driven ApproachesShuai Wan, Shuhong Guan, Yunchao Tang · 2023 · Journal of Data Science and Intelligent Systems
- Visual Concrete Bridge Defect Classification and Detection Using Deep Learning: A Systematic ReviewDariush Amirkhani, Mohand Saïd Allili, Loucif Hebbache, Nadir Hammouche, Jean‐François Lapointe · 2024 · IEEE Transactions on Intelligent Transportation Systems
- An Integrated CNN-RNN Framework to Assess Road CrackTawsin Uddin Ahmed, Mohammad Shahadat Hossain, Md. Jahangir Alam, Karl Andersson · 2019 · International Conference on Computer and Information Technology (ICCIT)
- Automated crack segmentation via saturation channel thresholding, area classification and fusion of modified level set segmentation with Canny edge detectionUche A. Nnolim · 2020 · Heliyon
- Introduction of Deep Learning in Thermographic Monitoring of Cultural Heritage and Improvement by Automatic Thermogram Pre-Processing AlgorithmsIván Garrido, Jorge Erazo-Aux, S. Lagüela, Стефано Сфарра, Clemente Ibarra‐Castanedo, Elena Pivarčiová, Gianfranco Gargiulo, Xavier Maldague, Pedro Arias · 2021 · Sensors
- Thermal anomaly detection in walls via CNN-based segmentationGwanyong Park, Minhyung Lee, Hyang-In Jang, Changmin Kim · 2021 · Automation in Construction
- Convolutional neural network for predicting crack pattern and stress-crack width curve of air-void structure in 3D printed concreteZe Chang, Zhi Wan, Yading Xu, Erik Schlangen, Branko Šavija · 2022 · Engineering Fracture Mechanics