Fig. 2. CNN architecture.
This architecture begins with a single input patch of size 256×256x with a corresponding output of 6th order SH coefficients (1×28). The network consists of four convolutional layers with subsequent down-sampling and flattened towards the end to a fully connected dense layer. Relu activation, batch normalization and max pooling have been used for all convolutional layers.