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Hyperspectral image classification based on optimized convolutional neural networks with 3D stacked blocks

文献类型：期刊论文

作者Zhang, Xiaoxia1; Guo, Yong2; Zhang, Xia1
刊名EARTH SCIENCE INFORMATICS
出版日期2022-01-11
页码13
关键词Convolutional neural network 3D convolution Hyperspectral image classification Stacked blocks Attention mechanism Spectral-spatial characteristics
ISSN号1865-0473
DOI10.1007/s12145-021-00731-1
通讯作者Zhang, Xiaoxia(2017010117@stu.cdut.edu.cn)
英文摘要3D convolution can fully utilize the spectral-spatial characteristics of hyperspectral image (HSI), and stacked blocks with deep layers are capable of extracting hidden features and utilizing discriminant information for classification. Naturally, a 3D convolutional neural network (CNN) based on stacked blocks named SB-3D-CNN is presented for HSI classification. Moreover, the proposed network introduces the attention mechanism before the fully connected layer, which can filter out interfering information effectively. Then we optimized the architecture to obtain optimal results on three commonly used datasets of Indian Pines, Salinas and Pavia University. Experimental results demonstrate that the optimized architecture achieves better classification rates than related recent works. Because the classification accuracies on the three datasets have reached saturation, we transferred the optimized architecture to a more complex dataset adopting the airborne hyperspectral data, which obtains from Guangxi province in south China. The results show that the optimized architecture achieves superior classification accuracies compared with other state-of-the-art methods. These results also demonstrate the optimized SB-3D-CNN has the advantages of validity and portability to more complex data.
WOS研究方向Computer Science ; Geology
语种英语
WOS记录号WOS:000741604200001
出版者SPRINGER HEIDELBERG
源URL[http://119.78.100.138/handle/2HOD01W0/14918]  
专题中国科学院重庆绿色智能技术研究院
通讯作者Zhang, Xiaoxia
作者单位1.Chengdu Univ Technol, Minist Educ, Key Lab Earth Explorat & Informat Technol, Coll Geophys, Chengdu, Peoples R China
2.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Inst Intelligent Mfg Technol, Chongqing, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Xiaoxia,Guo, Yong,Zhang, Xia. Hyperspectral image classification based on optimized convolutional neural networks with 3D stacked blocks[J]. EARTH SCIENCE INFORMATICS,2022:13.
APA Zhang, Xiaoxia,Guo, Yong,&Zhang, Xia.(2022).Hyperspectral image classification based on optimized convolutional neural networks with 3D stacked blocks.EARTH SCIENCE INFORMATICS,13.
MLA Zhang, Xiaoxia,et al."Hyperspectral image classification based on optimized convolutional neural networks with 3D stacked blocks".EARTH SCIENCE INFORMATICS (2022):13.

入库方式： OAI收割

来源：重庆绿色智能技术研究院

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