Automatic detection of defects in concrete structures based on deep learning

This publication has 17 references indexed in Scilit:

• Deep learning‐based multi‐class damage detection for autonomous post‐disaster reconnaissance
  Structural Control and Health Monitoring, 2020
• Concrete bridge surface damage detection using a single-stage detector
  Computer-Aided Civil and Infrastructure Engineering, 2019
• Automatic crack detection for tunnel inspection using deep learning and heuristic image post-processing
  Applied Intelligence, 2019
• Zernike-moment measurement of thin-crack width in images enabled by dual-scale deep learning
  Computer-Aided Civil and Infrastructure Engineering, 2018
• Image-based post-disaster inspection of reinforced concrete bridge systems using deep learning with Bayesian optimization
  Computer-Aided Civil and Infrastructure Engineering, 2018
• Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete
  Construction and Building Materials, 2018
• Early-Age Cracking in Concrete: Causes, Consequences, Remedial Measures, and Recommendations
  Applied Sciences, 2018
• Autonomous Structural Visual Inspection Using Region‐Based Deep Learning for Detecting Multiple Damage Types
  Computer-Aided Civil and Infrastructure Engineering, 2017
• The Pascal Visual Object Classes (VOC) Challenge
  International Journal of Computer Vision, 2009
• Evaluating Pavement Cracks with Bidimensional Empirical Mode Decomposition
  EURASIP Journal on Advances in Signal Processing, 2008