Improved convolutional neural network in remote sensing image classification

被引：0
作者：
Binghui Xu
机构：
[1] Taizhou Vocational & Technical College,
来源：
Neural Computing and Applications | 2021年 / 33卷
关键词：
Convolutional neural network; Algorithm improvement; Remote sensing image; Image classification; Image recognition;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The classification of land cover is the first step in the analysis and application of remote sensing data in land resources. How to solve the multi-category image recognition and meet certain precision is a key issue in remote sensing image research, which has very important theoretical significance and practical application value. In this study, the algorithm is improved on the basis of convolutional neural network, and experiments are carried out on multi-source remote sensing images with different geomorphologies taken under three different weather conditions to verify the effectiveness and scalability of the improved convolutional neural network. The research results show that the improved algorithm proposed in this paper has certain results in remote sensing image classification and can provide theoretical reference for subsequent related research.
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收藏
页码：8169 / 8180
页数：11
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