卷积神经网络在SAR遥感海冰分类中的应用可行性分析 |
作者:崔艳荣1 邹斌1 2 3 韩震1 石立坚2 3 刘森2 |
单位:1. 上海海洋大学海洋科学学院, 上海 201306; 2. 国家卫星海洋应用中心, 北京 100081; 3. 国家海洋局空间海洋遥感与应用研究重点实验室, 北京 100081 |
关键词:卫星遥感 海冰分类 应用 卷积神经网络 深度学习 |
分类号:P731.15 |
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出版年·卷·期(页码):2019·36·第五期(77-85) |
摘要:
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分别介绍了卫星遥感海冰监测、分类的传统方法,以及卷积神经网络在遥感影像分类识别中的应用成果。尝试将在图像识别、语言检测等方面取得成功的卷积神经网络算法应用在海冰图像分类中,利用其能够应对非线性、网络结构简单、可并行运算等能力去解决海冰数据分类问题。 |
This paper analyzes the traditional methods of sea ice monitoring and classification based on satellite remote sensing, and the application results of convolutional neural network in remote sensing image classification and recognition. Moreover, the convolutional neural networks algorithm, which has been successfully used in image recognition and language detection, is applied to the classification of sea ice images, and to solve the issues of sea ice data classification based on its simple network structure, capability in coping with nonlinearity and parallel computing. |
参考文献:
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