Meteorology studies the behaviour of atmospheric phenomena in a specific place and time, it is of enormous dynamism and complexity. This paper presents an approach based on a deep semantic neural network that accurately performs a multi-class pixel-wise classification of diverse cloud types, providing information of great value to complement traditional weather assessment techniques. The obtained results suggest that simple web-cams can be of great help for observations that complement traditional data for short-term weather predictions and generations of warnings.
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