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Cloud Type Distinction Based on CNN: an Aid for Short-Term Weather Forecast

Miguel Martin-Abadal,Yolanda Gonzalez-Cid, Joan Roig-Nomura, Jose Jesus Manas, Attila Nagy, Tomas Salom, Carlos Alonso

CCIA(2019)

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Abstract
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 multiclass 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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Key words
deep learning,convolutional neural networks (CNN),semantic segmentation,pixel-wise cloud classification,meteorology
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