3D Convolutional neural network model in TensorFlow

Description

# Input Layer for patches of different sizes

# First convolution, batch normalization and max pool

# Second convolution, batch normalization and max pool

# Two Final Dense Layers

# set up for predictions 

# Calculate Loss

# Define Optimizer

# Add evaluation metrics (for EVAL mode)

3D World Editor in Simulink

Real-Time 3D Reconstruction of Dexterous Continuum Surgical Robots