Deep Convolutional Activations-Based Features for Ground-Based Cloud Classification

doi:10.1109/LGRS.2017.2681658

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 影像分析与机器视觉团队

	Deep Convolutional Activations-Based Features for Ground-Based Cloud Classification
	Shi, Cunzhao1 ; Wang, Chunheng1 ; Wang, Yu1,2 ; Xiao, Baihua1
刊名	IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
	2017-06-01
卷号	14 期号:6 页码:816-820
关键词	Cloud Classification Convolutional Activations Convolutional Neural Network (Cnn) Fine-tune Max Pooling Sum Pooling
DOI	10.1109/LGRS.2017.2681658
文献子类	Article
英文摘要	Ground-based cloud classification is crucial for meteorological research and has received great concern in recent years. However, it is very challenging due to the extreme appearance variations under different atmospheric conditions. Although the convolutional neural networks have achieved remarkable performance in image classification, no one has evaluated their suitability for cloud classification. In this letter, we propose to use the deep convolutional activations-based features (DCAFs) for ground-based cloud classification. Considering the unique characteristic of cloud, we believe the local rich texture information might be more important than the global layout information and, thus, give a comprehensive evaluation of using both shallow convolutional layers-based features and DCAFs. Experimental results on two challenging public data sets demonstrate that although the realization of DCAF is quite straightforward without any use-dependent tricks, it outperforms conventional hand-crafted features considerably.
WOS关键词	IMAGES ; RECOGNITION
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
WOS记录号	WOS:000402092300006
资助机构	National Natural Science Foundation of China(61531019 ; 61601462 ; 71621002)
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/15125]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_影像分析与机器视觉团队
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Shanxi Univ, Sch Software, Taiyuan 030006, Peoples R China
推荐引用方式 GB/T 7714	Shi, Cunzhao,Wang, Chunheng,Wang, Yu,et al. Deep Convolutional Activations-Based Features for Ground-Based Cloud Classification[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2017,14(6):816-820.
APA	Shi, Cunzhao,Wang, Chunheng,Wang, Yu,&Xiao, Baihua.(2017).Deep Convolutional Activations-Based Features for Ground-Based Cloud Classification.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,14(6),816-820.
MLA	Shi, Cunzhao,et al."Deep Convolutional Activations-Based Features for Ground-Based Cloud Classification".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 14.6(2017):816-820.