  We describe a new neural-network technique developed for an automated
recognition of solar filaments visible in the hydrogen H-alpha line full disk
spectroheliograms. This technique allows neural networks learn from a few image
fragments labelled manually to recognize the single filaments depicted on a
local background. The trained network is able to recognize filaments depicted
on the backgrounds with variations in brightness caused by atmospherics
distortions. Despite the difference in backgrounds in our experiments the
neural network has properly recognized filaments in the testing image
fragments. Using a parabolic activation function we extend this technique to
recognize multiple solar filaments which may appear in one fragment.
