Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 17, issue 3
Articles | Volume 17, issue 3
https://doi.org/10.5194/amt-17-979-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-979-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 3
Research article
 | 
09 Feb 2024
Research article |  | 09 Feb 2024

Improved RepVGG ground-based cloud image classification with attention convolution

Chaojun Shi, Leile Han, Ke Zhang, Hongyin Xiang, Xingkuan Li, Zibo Su, and Xian Zheng

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Latest update: 13 Dec 2024
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Short summary
This article mainly studies the problem of ground cloud classification and significantly improves the accuracy of ground cloud classification by applying an improved deep-learning method. The research results show that the method proposed in this article has a significant impact on the classification results of ground cloud images. These conclusions have important implications for providing new insights and future research directions in the field of ground cloud classification.
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