u_net_double_conv2d: Creates a double convolutional U-Net block.
In maju116/platypus: Tools for Computer Vision in R

Creates a double convolutional U-Net block.

u_net_double_conv2d(
  input,
  filters,
  kernel_size,
  batch_normalization = TRUE,
  kernel_initializer = "he_normal"
)

`input`	Model or layer object.
`filters`	Integer, the dimensionality of the output space (i.e. the number of output filters in the convolution).
`kernel_size`	An integer or list of 2 integers, specifying the width and height of the 2D convolution window. Can be a single integer to specify the same value for all spatial dimensions.
`batch_normalization`	Should batch normalization be used in the block.
`kernel_initializer`	Initializer for the kernel weights matrix.