科技创新与应用2025，Vol.15Issue(18)：22-28,7.DOI:10.19981/j.CN23-1581/G3.2025.18.005
基于机器学习与深度学习的地基云识别进展
摘要
Abstract
With the rapid development of deep learning technology,transfer learning has also been successfully applied in the field of image processing based on deep learning.In order to verify the feasibility of deep learning technology combined with transfer learning in ground-based cloud species identification,and the effectiveness and advancement compared with traditional machine learning methods,this paper conducts machine learning and transfer deep learning on the SWIMCAT ground-based cloud dataset.Experimental comparison of learning methods,experimental comparison of transfer learning and non-transfer learning,and visual analysis of the characteristics of ground-based clouds in convolutional neural networks.The advantages and disadvantages of machine learning and transfer deep learning in ground-based cloud recognition are compared and analyzed through experiments,laying a theoretical foundation for subsequent in-depth research on deep learning ground-based cloud recognition algorithms.关键词
深度学习/迁移学习/机器学习/地基云图/可视化Key words
deep learning/transfer learning/machine learning/ground-based cloud map/visualization分类
信息技术与安全科学引用本文复制引用
曹冉,王敏,王佳锋,谷文杰,黎永顺..基于机器学习与深度学习的地基云识别进展[J].科技创新与应用,2025,15(18):22-28,7.基金项目
国家自然科学基金资助项目(41775165,U22B2002) （41775165,U22B2002）
安徽省高校杰出青年科研项目(2023AH020022) （2023AH020022）
