CloudFU-Net: A Fine-Grained Segmentation Method for Ground-Based Cloud Images Based on an Improved Encoder-Decoder Structure

The segmentation of ground-based cloud image is a crucial aspect of ground-based cloud observation, with significant implications for meteorological forecasting, photovoltaic power prediction, and other related tasks. At present, the proposed method of ground-based cloud image segmentation only sepa...

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Bibliographic Details
Published in:	IEEE transactions on geoscience and remote sensing Vol. 62; pp. 1 - 13
Main Authors:	Shi, Chaojun, Su, Zibo, Zhang, Ke, Xie, Xiongbin, Zheng, Xian, Lu, Qiaochu, Yang, Jiyuan
Format:	Journal Article
Language:	English
Published:	New York IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Cloud computing Clouds Coders Decoding Dilated convolution fine-grained segmentation of ground-based cloud ground-based cloud image dataset Ground-based observation Image processing Image segmentation Irradiance Kitchenware Meteorologists photovoltaic power prediction Photovoltaic systems Photovoltaics Predictions selective kernel (SK) attention Semantics Solar irradiance Solar radiation Weather forecasting
ISSN:	0196-2892, 1558-0644
Online Access:	Get full text
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