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YUN: A Fast Ground-to-air Cloud Image Recognition Framework | IEEE Conference Publication | IEEE Xplore

YUN: A Fast Ground-to-air Cloud Image Recognition Framework


Abstract:

The recognition of cloud maps plays an important role in the field of meteorological prediction. The mainstream recognition of cloud maps mainly focuses on satellite clou...Show More

Abstract:

The recognition of cloud maps plays an important role in the field of meteorological prediction. The mainstream recognition of cloud maps mainly focuses on satellite cloud maps, while research on ground-to-air cloud maps is less. In this paper, we propose an analysis framework - YUN - to quickly locate and identify clouds in these maps. A Quick Cloud region Proposal(QCP) was designed to segment cloud maps to the greatest extent. Then we use the convolutional neural network to extract features of the cloud maps and use fully connected network to predict the type of cloud. In addition, a voting mechanism with a variety of methods has achieved good prediction results.
Date of Conference: 06-08 May 2019
Date Added to IEEE Xplore: 08 August 2019
ISBN Information:
Conference Location: Porto, Portugal

References

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