关键词: 卷积神经网络（CNN）, 影像分割, 影像分类, 迁移学习

Abstract: Deep learning shows excellent performance in image recognition and natural language processing. This paper presents a learning method which is based on Convolution Neural Network（CNN） to classify remote sensing images. Aiming at the problem of low efficiency caused by too many sampling windows in remote sensing image classification, this paper proposes a novel method based on region to improve the classification efficiency. There are two steps in the classification process. The first step of the proposed algorithm is to classify the input images by convolution neural networks. Then, SVM is used to classify the results of convolution neural networks. The proposed algorithm is evaluated by being compared with the results of other existing methods. Experimental results show that proposed algorithm can achieve higher classification accuracy.

Key words: Convolution Neural Networks（CNN）, image segmentation, image classification, transfer learning