Bayesian Deep Learning For Manufacturing (dlmfg)
2.0.0
  • Installation and Implementation
  • Real System Implementation (3D Optical Scanner: WLS400A)
  • Library Configuration
  • Data Description & Processing
  • Model Architecture
  • Deep Reinforcement Learning for Control and Correction
  • Model Architecture Selection
  • Bayesian Deep Learning
  • 3D U-Net Architecture Global Interpretability
  • 3D U-Net Architecture Local Interpretability
  • 3D U-Net Segmentation
  • Class Structure: Objects and Methods
  • Key Measurement Characteristics (KMCs)
  • Utilities
  • Continual and Transfer Learning
  • Active Learning/Adaptive Sampling
  • Visualization
  • Case Study: Positioning and Clamping Variations for Halo
  • Case Study: Door Inner and Hinge Reinforcement Multi-Stage Assembly
  • Case Study: Cross Member Multi-Station Assembly
  • Research and References
Bayesian Deep Learning For Manufacturing (dlmfg)
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