A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure

Koch, Christian, Georgieva, Kristina, Kasireddy, Varun, Akinci, Burcu, Fieguth, Paul·2015·Advanced Engineering Informatics

Cited by (1,000)

Items 101–200 of 1,000

  1. Improvement of Lightweight Convolutional Neural Network Model Based on YOLO Algorithm and Its Research in Pavement Defect Detection
    Fujun Du, Shuangjian Jiao · 2022 · Sensors
  2. Automatic Pavement Crack Detection and Classification Using Multiscale Feature Attention Network
    Song Wei-dong, Guohui Jia, Di Jia, Hong Zhu · 2019 · IEEE Access
  3. PEER Hub ImageNet: A Large-Scale Multiattribute Benchmark Data Set of Structural Images
    Yuqing Gao, Khalid M. Mosalam · 2020 · Journal of Structural Engineering
  4. Rethinking Road Surface 3-D Reconstruction and Pothole Detection: From Perspective Transformation to Disparity Map Segmentation
    Rui Fan, Umar Ozgunalp, Yuan Wang, Ming Liu, Ioannis Pitas · 2021 · IEEE Transactions on Cybernetics
  5. Automated defect inspection of concrete structures
    Jun Kang Chow, Kuan-Fu Liu, Pin Siang Tan, Zhaoyu Su, Jimmy Wu, Zhaofeng Li, Yu-Hsing Wang · 2021 · Automation in Construction
  6. Visual analysis of asphalt pavement for detection and localization of potholes
    Muhammad Haroon Yousaf, Kanza Azhar, Fiza Murtaza, Fawad Hussain · 2018 · Advanced Engineering Informatics
  7. Crack Detection from a Concrete Surface Image Based on Semantic Segmentation Using Deep Learning
    Tatsuro Yamane, Pang‐jo Chun · 2020 · Journal of Advanced Concrete Technology
  8. A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection
    Shelly Sheynin, Sagie Benaim, Lior Wolf · 2021 · IEEE/CVF International Conference on Computer Vision (ICCV)
  9. An Automatic Image Processing Algorithm Based on Crack Pixel Density for Pavement Crack Detection and Classification
    Nima Safaei, Omar Ghaleb Smadi, Arezoo Masoud, Babak Safaei · 2021 · International Journal of Pavement Research and Technology
  10. Convolutional neural network for pothole detection in asphalt pavement
    Wanli Ye, Wei Jiang, Tong Zheng, Dongdong Yuan, Jingjing Xiao · 2019 · Road Materials and Pavement Design
  11. Façade defects classification from imbalanced dataset using meta learning-based convolutional neural network
    Jingjing Guo, Qian Wang, Yiting Li, Pengkun Liu · 2020 · Computer-Aided Civil and Infrastructure Engineering
  12. Automatic tunnel lining crack detection via deep learning with generative adversarial network-based data augmentation
    Zhong Zhou, Junjie Zhang, Chenjie Gong, Wei Wu · 2022 · Underground Space
  13. Inspecting Buildings Using Drones and Computer Vision: A Machine Learning Approach to Detect Cracks and Damages
    Hafiz Suliman Munawar, Fahim Ullah, Amirhossein Heravi, Muhammad Jamaluddin Thaheem, Ahsen Maqsoom · 2021 · Drones
  14. Metaheuristic Optimized Edge Detection for Recognition of Concrete Wall Cracks: A Comparative Study on the Performances of Roberts, Prewitt, Canny, and Sobel Algorithms
    Nhat‐Duc Hoang, Quoc-Lam Nguyen · 2018 · Advances in Civil Engineering
  15. Lightweight semantic segmentation of complex structural damage recognition for actual bridges
    Yang Xu, Yunlei Fan, Hui Li · 2023 · Structural Health Monitoring
  16. Vision-based defects detection for bridges using transfer learning and convolutional neural networks
    Jinsong Zhu, Chi Zhang, Haidong Qi, Ziyue Lu · 2019 · Structure and Infrastructure Engineering
  17. A High-Efficiency Fully Convolutional Networks for Pixel-Wise Surface Defect Detection
    Lingteng Qiu, Xiaojun Wu, Zhiyang Yu · 2019 · IEEE Access
  18. Recent computer vision applications for pavement distress and condition assessment
    Ayman H. El Hakea, Mohamed Waleed Fakhr · 2022 · Automation in Construction
  19. Deep learning models for bridge deck evaluation using impact echo
    Sattar Dorafshan, Hoda Azari · 2020 · Construction and Building Materials
  20. Deep learning-based instance segmentation of cracks from shield tunnel lining images
    Hongwei Huang, Shuai Zhao, Dongming Zhang, Jiayao Chen · 2020 · Structure and Infrastructure Engineering
  21. Review on automated quality inspection of precast concrete components
    Zhiliang Ma, Yu Liu, Jiayi Li · 2023 · Automation in Construction
  22. Computer vision-based method for concrete crack detection
    Tran Hiep Dinh, Quang Phuc Ha, Hung Manh La · 2016 · International Conference on Control, Automation, Robotics and Vision (ICARCV)
  23. Real-time smart video surveillance to manage safety: A case study of a transport mega-project
    Hanbin Luo, Jiajing Liu, Weili Fang, Peter E.D. Love, Qunzhou Yu, Zhenchuan Lu · 2020 · Advanced Engineering Informatics
  24. Performance of Machine Learning Algorithms in Predicting the Pavement International Roughness Index
    Mohammad Z. Bashar, Cristina Torres-Machí · 2021 · Transportation Research Record Journal of the Transportation Research Board
  25. A framework of pavement management system based on IoT and big data
    Jichang Dong, Weina Meng, Ying Liu, Jing Ti · 2021 · Advanced Engineering Informatics
  26. Revolutionizing concrete analysis: An in-depth survey of AI-powered insights with image-centric approaches on comprehensive quality control, advanced crack detection and concrete property exploration
    Kaustav Sarkar, Amit Shiuly, Krishna Gopal Dhal · 2023 · Construction and Building Materials
  27. Vibration-based semantic damage segmentation for large-scale structural health monitoring
    Seyed Omid Sajedi, Xiao Ping Liang · 2019 · Computer-Aided Civil and Infrastructure Engineering
  28. Artificial Intelligence Assisted Infrastructure Assessment using Mixed Reality Systems
    Enes Karaaslan, Ulaş Bağcı, F. Necati Çatbaş · 2019 · Transportation Research Record Journal of the Transportation Research Board
  29. Review on Computer Aided Sewer Pipeline Defect Detection and Condition Assessment
    Saeed Moradi, Tarek M. Zayed, Farzaneh Golkhoo · 2019 · Infrastructures
  30. Concrete Crack Detection Based on Well-Known Feature Extractor Model and the YOLO_v2 Network
    Shuai Teng, Zongchao Liu, Gongfa Chen, Cheng Li · 2021 · Applied Sciences
  31. Improved bare PCB defect detection approach based on deep feature learning
    Can Zhang, Wei Shi, Xiaofei Li, Haijian Zhang, Hong Liu · 2018 · The Journal of Engineering
  32. Automated Vision Systems for Condition Assessment of Sewer and Water Pipelines
    Rakiba Rayhana, Yutong Jiao, Amirhossein Zaji, Zheng Liu · 2020 · IEEE Transactions on Automation Science and Engineering
  33. A Review of Vision-Based Pothole Detection Methods Using Computer Vision and Machine Learning
    Yashar Safyari, Masoud Mahdianpari, Hodjat Shiri · 2024 · Sensors
  34. Real-Time Dense Stereo Embedded in a UAV for Road Inspection
    Rui Fan, Jianhao Jiao, Jie Pan, Huaiyang Huang, Shaojie Shen, Ming Liu · 2019 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  35. Attention-guided analysis of infrastructure damage with semi-supervised deep learning
    Enes Karaaslan, Ulaş Bağcı, F. Necati Çatbaş · 2021 · Automation in Construction
  36. Tunnel lining crack detection model based on improved YOLOv5
    Shuqian Duan, Minghuan Zhang, Shili Qiu, Jiecheng Xiong, Hao Zhang, Chenyang Li, Quan Jiang, Yongyuan Kou · 2024 · Tunnelling and Underground Space Technology
  37. Image-Based Crack Detection Using Crack Width Transform (CWT) Algorithm
    Hyun-Woo Cho, Hyuk-Jin Yoon, Ju-Yeong Jung · 2018 · IEEE Access
  38. Automatic Crack Detection using Mask R-CNN
    Leanne Attard, Carl James Debono, Gianluca Valentino, Mario Di Castro, A. Masi, Luigi Scibile · 2019 · International symposium on image and signal processing and analysis/ISPA ...
  39. Detection of Flaws in Concrete Using Ultrasonic Tomography and Convolutional Neural Networks
    Marek Słoński, Krzysztof Schabowicz, Ewa Krawczyk · 2020 · Materials
  40. Adaptive wavelet neural network for terrestrial laser scanner-based crack detection
    Yelda Türkan, Jonathan Hong, Simon Laflamme, Nisha Puri · 2018 · Automation in Construction
  41. Vision-based Structural Inspection using Multiscale Deep Convolutional Neural Networks
    Vedhus Hoskere, Yasutaka Narazaki, Tu A. Hoang, Billie F. Spencer · 2018 · arXiv (Cornell University)
  42. Improvement of Damage Segmentation Based on Pixel-Level Data Balance Using VGG-Unet
    Jiyuan Shi, Ji Dang, Mida Cui, Rongzhi Zuo, Kazuhiro Shimizu, Akira Tsunoda, Yasuhíro Suzuki · 2021 · Applied Sciences
  43. Evaluation of Detection Approaches for Road Anomalies Based on Accelerometer Readings—Addressing Who’s Who
    M. Ricardo Carlos, Mario Ezra Aragón, Luis C. González, Hugo Jair Escalante, Fernando Martínez · 2018 · IEEE Transactions on Intelligent Transportation Systems
  44. Attribute-based structural damage identification by few-shot meta learning with inter-class knowledge transfer
    Yang Xu, Yuequan Bao, Yufeng Zhang, Hui Li · 2020 · Structural Health Monitoring
  45. Automatic pixel‐level crack detection and evaluation of concrete structures using deep learning
    Weijian Zhao, Yunyi Liu, Jiawei Zhang, Yi Shao, Jiangpeng Shu · 2022 · Structural Control and Health Monitoring
  46. Automatic crack detection on concrete and asphalt surfaces using semantic segmentation network with hierarchical Transformer
    Hubing Li, Haowei Zhang, Hong Zhu, Kang Gao, Hanbin Liang, Jiangjin Yang · 2024 · Engineering Structures
  47. Sam-based instance segmentation models for the automation of structural damage detection
    Zehao Ye, Lucy Lovell, Asaad Faramarzi, Jelena Ninić · 2024 · Advanced Engineering Informatics
  48. Development of an Artificial Intelligence Model to Recognise Construction Waste by Applying Image Data Augmentation and Transfer Learning
    Seunguk Na, Seokjae Heo, Sehee Han, Yoon-Soo Shin, Myeunghun Lee · 2022 · Buildings
  49. Fully Convolutional Networks for Surface Defect Inspection in Industrial Environment
    Yu, Zhiyang, Wu, Xiaojun, Gu, Xiaodong · 2017 · Lecture Notes in Computer Science
  50. Deep Learning-Based Applications for Safety Management in the AEC Industry: A Review
    Hou, Lei, Chen, Haosen, Zhang, Guomin (Kevin), Wang, Xiangyu · 2021 · Applied Sciences
  51. Investigation of steel frame damage based on computer vision and deep learning
    Bubryur Kim, Naveen Raj Yuvaraj, Hee Won Park, K. R. Sri Preethaa, Ramaraj Pandian, Dong‐Eun Lee · 2021 · Automation in Construction
  52. Experimental and numerical studies for suitable infrared thermography implementation on concrete bridge decks
    Shuhei Hiasa, Recep Birgül, Masato Matsumoto, F. Necati Çatbaş · 2018 · Measurement
  53. In situ crack mapping of large-scale self-sensing concrete pavements using electrical resistance tomography
    Sumit Gupta, Yun-An Lin, Han‐Joo Lee, Jeffrey Buscheck, Rongzong Wu, Jerome Peter Lynch, Navneet Garg, Kenneth J. Loh · 2021 · Cement and Concrete Composites
  54. A new rail inspection method based on deep learning using laser cameras
    Yunus Santur, Mehmet Karaköse, Erhan Akın · 2017 · International Artificial Intelligence and Data Processing Symposium (IDAP)
  55. Automated wall‐climbing robot for concrete construction inspection
    Liang Yang, Bing Li, Jinglun Feng, Guoyong Yang, Chang Yong, Biao Jiang, Jizhong Xiao · 2022 · Journal of Field Robotics
  56. Automatic internal crack detection from a sequence of infrared images with a triple-threshold Canny edge detector
    Wang Gaochao, Peter Wai-Tat Tse, Maodan Yuan · 2017 · Measurement Science and Technology
  57. A fast adaptive crack detection algorithm based on a double-edge extraction operator of FSM
    Qijun Luo, Baozhen Ge, Qingguo Tian · 2019 · Construction and Building Materials
  58. A Terrestrial LiDAR-Based Detection of Shape Deformation for Maintenance of Bridge Structures
    Gichun Cha, Seunghee Park, Tae Keun Oh · 2019 · Journal of Construction Engineering and Management
  59. We Learn Better Road Pothole Detection: From Attention Aggregation to Adversarial Domain Adaptation
    Rui Fan, Hengli Wang, Mohammud J. Bocus, Ming Liu · 2020 · Lecture notes in computer science
  60. Review of constraints and critical success factors of developing urban underground space
    Yani Lai, Yuling Wang, Jing Qiu Cheng, Xiangsheng Chen, Quan Liu · 2023 · Underground Space
  61. Towards Low-Cost Pavement Condition Health Monitoring and Analysis Using Deep Learning
    Roberts, Ronald, Giancontieri, Gaspare, Inzerillo, Laura, Di Mino, Gaetano · 2020 · Applied Sciences
  62. Detection of Road-Surface Anomalies Using a Smartphone Camera and Accelerometer
    Taehee Lee, Chanjun Chun, Seung-Ki Ryu · 2021 · Sensors
  63. An image enhancement algorithm to improve road tunnel crack transfer detection
    Jian Liu, Zhiyuan Zhao, Chengshun Lv, Yunfeng Ding, Honglei Chang, Quanyi Xie · 2022 · Construction and Building Materials
  64. Image Processing Techniques for Concrete Crack Detection: A Scientometrics Literature Review
    Md. Al-Masrur Khan, Seong‐Hoon Kee, Al‐Sakib Khan Pathan, Abdullah-Al Nahid · 2023 · Remote Sensing
  65. A Short Review on Supervised Machine Learning and Deep Learning Techniques in Computer Vision
    Ahmed Adil Nafea, Saeed Amer Alameri, Russel R. Majeed, Meaad Ali Khalaf, Mohammed M AL-Ani · 2024 · Babylonian Journal of Machine Learning
  66. Machine Learning Applications in Road Pavement Management: A Review, Challenges and Future Directions
    Tiago Tamagusko, Matheus Gomes Correia, Adelino Ferreira · 2024 · Infrastructures
  67. Investigation of effective utilization of infrared thermography (IRT) through advanced finite element modeling
    Shuhei Hiasa, Recep Birgül, F. Necati Çatbaş · 2017 · Construction and Building Materials
  68. Pixel-Wise Crack Detection Using Deep Local Pattern Predictor for Robot Application
    Yundong Li, Hongguang Li, Hongren Wang · 2018 · Sensors
  69. Cable surface damage detection in cable-stayed bridges using optical techniques and image mosaicking
    Xinke Li, Chao Gao, Yongcai Guo, Fuliang He, Yanhua Shao · 2018 · Optics & Laser Technology
  70. Towards automated detection and quantification of concrete cracks using integrated images and lidar data from unmanned aerial vehicles
    Yujie Yan, Zhong Mao, Jiahao Wu, Taşkın Padır, Jerome F. Hajjar · 2021 · Structural Control and Health Monitoring
  71. Review of Image-Based 3D Reconstruction of Building for Automated Construction Progress Monitoring
    Jingguo Xue, Xueliang Hou, Ying Zeng · 2021 · Applied Sciences
  72. Data-driven scene parsing method for recognizing construction site objects in the whole image
    Hongjo Kim, Kinam Kim, Hyoungkwan Kim · 2016 · Automation in Construction
  73. Pothole detection: An efficient vision based method using RGB color space image segmentation
    Amila Akagić, Emir Buza, Samir Omanović · 2017 · International Convention on Information and Communication Technology, Electronics and Microelectronics
  74. Increasing fracture toughness via architected porosity
    Kaitlynn M. Conway, Cody Kunka, Benjamin C. White, Garrett J. Pataky, Brad L. Boyce · 2021 · Materials & Design
  75. Automated crack pattern recognition from images for condition assessment of concrete structures
    Yiqing Liu, Justin K. W. Yeoh · 2021 · Automation in Construction
  76. DcsNet: a real-time deep network for crack segmentation
    Jie Pang, Hua Zhang, Hao Zhao, Linjing Li · 2022 · Signal Image and Video Processing
  77. Structural Health Monitoring of Concrete Bridges Through Artificial Intelligence: A Narrative Review
    Vijay Prakash, C. J. Debono, M. A. Musarat, R. P. Borg, Dylan Seychell, Wei Ding, Jiang-Peng Shu · 2025 · Applied Sciences
  78. Centralized predictive ceiling interaction control of quadrotor VTOL UAV
    Başaran Bahadır Koçer, Tegoeh Tjahjowidodo, Gerald Seet · 2018 · Aerospace Science and Technology
  79. Automating Data Collection for Robotic Bridge Inspections
    Stephen Phillips, Sriram Narasimhan · 2019 · Journal of Bridge Engineering
  80. State of the art in damage information modeling for RC bridges – A literature review
    Mathias Artus, Christian Koch · 2020 · Advanced Engineering Informatics
  81. Structural Load Estimation Using Machine Vision and Surface Crack Patterns for Shear-Critical RC Beams and Slabs
    Rouzbeh Davoudi, Gregory R. Miller, J. Nathan Kutz · 2018 · Journal of Computing in Civil Engineering
  82. Bottom-up image detection of water channel slope damages based on superpixel segmentation and support vector machine
    Junjie Chen, Donghai Liu · 2020 · Advanced Engineering Informatics
  83. Real-time sewer defect detection based on YOLO network, transfer learning, and channel pruning algorithm
    Zuxiang Situ, Shuai Teng, Xiaoting Liao, Gongfa Chen, Qianqian Zhou · 2023 · Journal of Civil Structural Health Monitoring
  84. Lightweight object detection network for multi‐damage recognition of concrete bridges in complex environments
    Tianyong Jiang, Lingyun Li, Bijan Samali, Yang Yu, Ke Huang, Wanli Yan, Lei Wang · 2024 · Computer-Aided Civil and Infrastructure Engineering
  85. An experimental study of the feasibility of phase‐based video magnification for damage detection and localisation in operational deflection shapes
    Marco Civera, Luca Zanotti Fragonara, Cecilia Surace · 2020 · Strain
  86. Crack segmentation through deep convolutional neural networks and heterogeneous image fusion
    Shanglian Zhou, Wei Song · 2021 · Automation in Construction
  87. Predictive equations for drift ratio and damage assessment of RC shear walls using surface crack patterns
    Hamed Momeni, Kiarash M. Dolatshahi · 2019 · Engineering Structures
  88. GPRI2Net: A Deep-Neural-Network-Based Ground Penetrating Radar Data Inversion and Object Identification Framework for Consecutive and Long Survey Lines
    Jing Wang, Hanchi Liu, Peng Jiang, Zhengfang Wang, Qingmei Sui, Fengkai Zhang · 2021 · IEEE Transactions on Geoscience and Remote Sensing
  89. Computer vision-based classification of concrete spall severity using metaheuristic-optimized Extreme Gradient Boosting Machine and Deep Convolutional Neural Network
    Hieu Nguyen, Nhat‐Duc Hoang · 2022 · Automation in Construction
  90. Leveraging computer vision towards high-efficiency autonomous industrial facilities
    Ibrahim Yousif, Liam Burns, Fadi El Kalach, R. Harik · 2024 · Journal of Intelligent Manufacturing
  91. Automated Bridge Inspection Using Mobile Ground Robotics
    Nicholas Charron, Evan McLaughlin, Stephen Phillips, Kevin Goorts, Sriram Narasimhan, Steven L. Waslander · 2019 · Journal of Structural Engineering
  92. Percussion‐based bolt looseness identification using vibration‐guided sound reconstruction
    Ying Ming Zhou, Shu-Yin Wang, Meng Zhou, Hongbing Chen, Cheng Yuan, Qingzhao Kong · 2021 · Structural Control and Health Monitoring
  93. Airport asphalt pavement health monitoring system for mechanical model updating and distress evaluation under realistic random aircraft loads
    Xianyong Ma, Zejiao Dong, Fengchen Chen, Huilun Xiang, Cheng Cao, Jianjun Sun · 2019 · Construction and Building Materials
  94. Human Intrusion Detection in Static Hazardous Areas at Construction Sites: Deep Learning–Based Method
    Xinyu Mei, Xiaojing Zhou, Feng Xu, Zhipeng Zhang · 2022 · Journal of Construction Engineering and Management
  95. Visual Concrete Bridge Defect Classification and Detection Using Deep Learning: A Systematic Review
    Dariush Amirkhani, Mohand Saïd Allili, Loucif Hebbache, Nadir Hammouche, Jean‐François Lapointe · 2024 · IEEE Transactions on Intelligent Transportation Systems
  96. Damage Detection and Finite-Element Model Updating of Structural Components through Point Cloud Analysis
    Kasra Ghahremani, Ali Khaloo, Sara Mohamadi, David Lattanzi · 2018 · Journal of Aerospace Engineering
  97. Prescriptive maintenance of prestressed concrete bridges considering digital twin and key performance indicator
    Chi-Ho Jeon, Chang-Su Shim, Yang-Hee Lee, Jennifer Mary Schooling · 2023 · Engineering Structures
  98. Large-Complex-Surface Defect Detection by Hybrid Gradient Threshold Segmentation and Image Registration
    Guang‐Zhong Cao, Songbo Ruan, Yeping Peng, Su‐Dan Huang, N. M. Kwok · 2018 · IEEE Access
  99. “Looking beneath the surface”: A visual-physical feature hybrid approach for unattended gauging of construction waste composition
    Junjie Chen, Weisheng Lu, Fan Xue · 2021 · Journal of Environmental Management
  100. Advanced bridge visual inspection using real-time machine learning in edge devices
    Mahta Zakaria, Enes Karaaslan, F. Necati Çatbaş · 2022 · Advances in Bridge Engineering