Ground-Based Cloud Detection Using Multiscale Attention Convolutional Neural Network
文献类型：期刊论文
| 作者 | Zhang, Zhong3; Yang, Shuzhen3; Liu, Shuang3; Xiao, Baihua1 ; Cao, Xiaozhong2
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| 刊名 | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
 |
| 出版日期 | 2021-08-26 |
| 页码 | 5 |
| ISSN号 | 1545-598X |
| 关键词 | Clouds Databases Decoding Cloud computing Convolutional neural networks Computer architecture Training Attention module cloud detection multiscale module Tianjin Normal University (TJNU) cloud detection database (TCDD) |
| DOI | 10.1109/LGRS.2021.3106337 |
| 通讯作者 | Liu, Shuang(shuangliu.tjnu@gmail.com) |
| 英文摘要 | Cloud detection plays a significant role in ground-based remote sensing observation, and it is quite challenging due to the variations in illumination and cloud form, and the vague boundaries between cloud and sky. In this letter, we propose a novel deep model named multiscale attention convolutional neural network (MACNN) for ground-based cloud detection, which possesses a symmetric encoder-decoder structure. For accurate cloud detection, we design the multiscale module in MACNN to obtain different receptive fields by using different hole rates for the filters, and meanwhile, we propose the attention module in MACNN to learn the attention coefficients in order to reflect different importance of pixels. Furthermore, we release the Tianjin Normal University (TJNU) cloud detection database (TCDD) to provide a comparative study for different methods, and to the best of our knowledge, it is the largest cloud detection database. We conduct a series of experiments on the TCDD, and the experimental results demonstrate that the proposed MACNN outperforms state-of-the-art methods in five quantitative evaluation criteria. |
| WOS关键词 | SEGMENTATION ; SYSTEM |
| 资助项目 | National Natural Science Foundation of China[62171321] ; Natural Science Foundation of Tianjin[20JCZDJC00180] ; Natural Science Foundation of Tianjin[19JCZDJC31500] ; Open Projects Program of National Laboratory of Pattern Recognition[202000002] ; Tianjin Higher Education Creative Team Funds Program |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:000732104900001 |
| 资助机构 | National Natural Science Foundation of China ; Natural Science Foundation of Tianjin ; Open Projects Program of National Laboratory of Pattern Recognition ; Tianjin Higher Education Creative Team Funds Program |
| 源URL | [http://ir.ia.ac.cn/handle/173211/46830]  |
| 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 |
| 通讯作者 | Liu, Shuang |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.China Meteorol Adm, Meteorol Observat Ctr, Beijing 100081, Peoples R China 3.Tianjin Normal Univ, Tianjin Key Lab Wireless Mobile Commun & Power Tr, Tianjin 300387, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Zhong,Yang, Shuzhen,Liu, Shuang,et al. Ground-Based Cloud Detection Using Multiscale Attention Convolutional Neural Network[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2021:5. |
| APA | Zhang, Zhong,Yang, Shuzhen,Liu, Shuang,Xiao, Baihua,&Cao, Xiaozhong.(2021).Ground-Based Cloud Detection Using Multiscale Attention Convolutional Neural Network.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,5. |
| MLA | Zhang, Zhong,et al."Ground-Based Cloud Detection Using Multiscale Attention Convolutional Neural Network".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2021):5. |
入库方式： OAI收割
来源：自动化研究所
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