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This is a good observation. My personal opinion is that using many smaller networks as components of a larger, manually engineered system could be a fruitful approach for these complex problems.

End-to-end deep learning is the holy grail -- and may ultimately happen -- but I don't think computation in silicon semiconductors is going to cut it, and we don't yet know what the next computational substrate will be.

Did you use a smallish convolutional model for extracting pole position, orientation, and radius from image data, or another approach?



If you're interested, here is a link to the initial paper: http://vader.cse.lehigh.edu/publications/fsr12_mon_per.pdf




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