  We use Deep Neural Networks (DNNs) to classify and reconstruct a large
database of handwritten digits from the intensity of the speckle patterns that
result after the images propagated through multimode fibers (MMF). Images
transmitted through fibers with up to 1km length were recovered. The ability of
the network to recognize the input degraded with fiber length but the
performance could be enhanced if the neural networks were trained to first
reconstruct the image and then classify it rather than classify it directly
from the speckle intensity.
