- Tail > Sparse Autoencoder
- Wings > Two CNNs
- Body > Non-Linear PCA
- Nose > MLP
CNN1 (Left Wing)
conv layers = 3
fc layers = 1
filter size = (1,4)
input channels = 1
output channels = 3
stride = 1
padding = none
output features = 15
CNN2 (Right Wing)
conv layers = 4
fc layers = 1
filter size = (1,3)
input channels = 1
output channels = 3
stride = 1
padding = none
output features = 15
Sparse AE (Tail)
linear layers = 8
dropout = 0.1
sparsity = 0.00005
output features = 15
NLPCA (Body)
input features = 108
linear layers = 3
output features = 15
MLP (Nose)
linear layers = 3