Deep Learning-Based Segmentation for Field Evaluation of Riprap and Large-Sized Aggregates

Keyphrases

• Evaluation Method 100%
• Large-sized 100%
• Segmentation Approach 100%
• Aggregate Material 100%
• Riprap 100%
• Deep Learning Segmentation 100%
• Image Data 50%
• Size-and-shape 50%
• Deformation Response 50%
• Image Segmentation 50%
• Morphological Properties 50%
• Deep Learning Methods 50%
• Size-dependent Properties 50%
• Engineering Application 50%
• Visual Inspection 50%
• Innovative Approach 50%
• Effective Field 50%
• Shape Properties 50%
• Practice Method 50%
• Layer Deformation 50%
• Particle Position 50%
• Medium Size 50%
• Performance Tuning 50%
• Aggregate Particles 50%
• Segmentation Framework 50%
• Ground Penetrating Radar 50%
• Aggregate Properties 50%
• Morphological Index 50%
• Wheel Loading 50%
• Object Detection Algorithm 50%
• Layer Modulus 50%
• Manual Measurement 50%
• Ballast Material 50%
• Art Objects 50%
• Evaluation Application 50%
• Image Segmentation Techniques 50%
• Object Segmentation 50%
• Aggregate Shape Properties 50%
• Aggregate Imaging System 50%
• Sieve Analysis 50%
• On-site Inspection 50%
• Mask R-CNN 50%
• Layer Strength 50%
• Inspection Checklist 50%
• Sustainable Performance 50%

Engineering

• Field Evaluation 100%
• Deep Learning 100%
• Individual Particle 40%
• Field Condition 40%
• Tasks 20%
• Good Agreement 20%
• Imaging Systems 20%
• Image Data 20%
• Deformation Response 20%
• Engineering Application 20%
• Effective Field 20%
• Visual Inspection 20%
• Ground Truth 20%
• Particle Aggregate 20%
• Manual Measurement 20%
• Segmentation Technique 20%
• Sustainable Performance 20%
• Site Inspection 20%

Material Science

• Morphology 100%
• Mechanical Strength 50%
• Ground-Penetrating Radar 50%