Abstract
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 deploys the artificial neural network (ANN) with one input and one output neurons and the two hidden neurons associated either with the filament or with background pixels in this fragment. The ANN learns to recognize the filament depicted on a local background from a single image fragment labelled manually. The trained neural network has properly recognized filaments in the testing image fragments depicted on backgrounds with various brightness caused by the atmospherics distortions. Using a parabolic activation function this technique was extended for recognition of multiple solar filaments occasionally appearing in selected fragments.
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Zharkova, V.V., Schetinin, V. (2003). A Neural-Network Technique for Recognition of Filaments in Solar Images. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_22
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DOI: https://doi.org/10.1007/978-3-540-45224-9_22
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