CASIA OpenIR  > 类脑智能研究中心
深度学习在航拍场景分类中的应用
李晓龙; 张兆翔; 王蕴红; 刘庆杰; Xiaolong Li
2014-03-01
发表期刊计算机科学与探索
卷号8期号:3页码:305-312
其他摘要In recent decades, aerial image/video processing has been widely studied for urban planning, coastal monitoring and military tasks. Therefore, understanding the contents contained in aerial images and studying the scene classification of aerial videos are very important. However, currently most popular scene classification algorithms are mainly for natural scenes, rarely for high resolution aerial scene classification. This paper proposes a hierarchical scene classification model for aerial videos/images. Firstly, the scale-invariant feature transform (SIFT) vector is extracted as the patch feature. Then, on the basis of utilizing bag of words, the deep belief network (DBN) initialized by restricted Boltzmann machine (RBM) is used to obtain the latent variables which describe the relationship between low-level region features and high-level global features. The DBN also plays as a classifier. The proposed method achieves promising performance compared with the state of art scene classification methods.
关键词Aerial Image Scene Classification Bags Of Feature Deep Learning High Resolution
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/13230
专题类脑智能研究中心
通讯作者Xiaolong Li
推荐引用方式
GB/T 7714
李晓龙,张兆翔,王蕴红,等. 深度学习在航拍场景分类中的应用[J]. 计算机科学与探索,2014,8(3):305-312.
APA 李晓龙,张兆翔,王蕴红,刘庆杰,&Xiaolong Li.(2014).深度学习在航拍场景分类中的应用.计算机科学与探索,8(3),305-312.
MLA 李晓龙,et al."深度学习在航拍场景分类中的应用".计算机科学与探索 8.3(2014):305-312.
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