Deep learning of 3D point clouds for detecting geometric defects in gears

Keyphrases

• 3D Metrology 40%
• 3D Point Cloud 100%
• Adaptive Measurement 20%
• Automated Analysis 20%
• Benchmark Dataset 20%
• Class Classification 20%
• Class Quality 20%
• Classification Performance 20%
• Control Activities 20%
• Control Task 20%
• Decision Task 20%
• Deep Learning 100%
• Deep Learning Architectures 20%
• Deep Learning Methods 20%
• Deep Learning Model 20%
• Defect Detection 20%
• Defect Region 20%
• Design Classification 20%
• Dimensional Accuracy 20%
• Gear Design 20%
• Gear Manufacturing 20%
• Geometrical Defects 100%
• High Dimension 20%
• High-resolution 20%
• Manufactured Products 20%
• Measurement Planning 20%
• Measurement Precision 20%
• Measurement Resolution 20%
• Modern Manufacturing 20%
• Multi-class 20%
• Part Design 40%
• Part-based 20%
• PointNet++ 20%
• Quality Assessment 20%
• Quality Classes 20%
• Quality Control 40%
• Recent Advancements 20%
• Shape Conformity 20%
• Sparsity 20%
• Surface Quality 20%
• Surface Shape 20%
• Widespread Adoption 20%

Engineering

• Classification Performance 20%
• Deep Learning Method 100%
• Defect Detection 20%
• Dimensional Accuracy 20%
• Dimensionality 20%
• Fine Scale 20%
• High Resolution 20%
• Measurement Resolution 20%
• Modern Manufacturing 20%
• Part Design 40%
• Point Cloud 100%
• Quality Control 40%
• Sparsity 20%
• Surface Quality 20%