CNN architecture. As explained in the text, it consists of five convolution layers composed of 64, 128, 128, 128, and 64 channels, including convolution, batch normalization, leaky ReLU activation (first three columns in light blue), maximum pooling, and Gaussian dropout (last two columns in dark blue). The last layer is followed by a fully connected layer (purple) and a classification layer returning a binary answer (1 for moon, 0 otherwise).