Multi-layers deep learning model with feature selection for automated detection and classification of highway pavement cracks

Keyphrases

• Feature Selection 100%
• Deep Learning Model 100%
• Convolutional Neural Network Model 100%
• Automated Classification 100%
• Automated Detection 100%
• Crack Detection 100%
• Pavement Crack 100%
• Highway Pavement 100%
• Feature Selection Methods 83%
• Training Model 50%
• Stochastic Gradient Descent with Momentum 50%
• Deep Learning Layer 50%
• RMSprop 50%
• Adaptive Moment Estimation 50%
• Optimization Algorithm 33%
• Particle Swarm Optimization 33%
• Fully Connected 33%
• Optimized Convolutional Neural Network 33%
• Design Methodology 16%
• Model Accuracy 16%
• High Performance 16%
• Optimization Techniques 16%
• Highly Accurate 16%
• Deep Learning 16%
• Pavement 16%
• Detector Response 16%
• Highly Effective 16%
• Artificial Intelligence Learning 16%
• Layer Model 16%
• Optimiser 16%
• Multiple Feature Selection 16%
• Systematic Application 16%
• Pavement Distress 16%
• Crack Evaluation 16%

Engineering

• Network Model 100%
• Feature Extraction 100%
• Crack Detection 100%
• Deep Learning Method 100%
• Convolutional Neural Network 100%
• Pavement 100%
• Selection Algorithm 50%
• Gradient Descent 50%
• Particle Swarm Optimization 33%
• Optimization Technique 16%
• Layer Model 16%
• Features Detection 16%
• Artificial Intelligence 16%