Can you give me a piece of advise of the network sructure that would be suitable for my task? I have 2 small images. They are basically the same, but differ in rotation and size. I should estimate the parameters for affine transform to get them similar. What network structure can be suitable for this task? For example, those based on convolutional networks did badly, because the pictures are too small.
Instead of NNs, you can use RANSAC algorithm to calculate homography matrix, but first you need to find feature points. However, if your images are blob-like, you may not get such a successful results. Here some presentations for better understanding: cs.umd notes and csail.mit notes
(Also, there might be better image processing tools.)