CloudU-Net: A Deep Convolutional Neural Network Architecture for Daytime and Nighttime Cloud Images’ Segmentation

IEEE Geoscience and Remote Sensing Letters(2021)

Cited 19|Views4
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Abstract
Cloud segmentation is one of the hot tasks in the field of weather forecast, environmental monitoring, site selection for observatory, and other areas. In this letter, we proposed a new deep convolutional neural network architecture called CloudU-Net for daytime and nighttime cloud images’ segmentation. The net consists of dilated convolution, activation, batch normalization (BN), max pooling, ups...
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Key words
Convolution,Image segmentation,Computer architecture,Clouds,Training,Kernel,Convolutional neural networks
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