Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Remote Sensing Technology and Application》 2017-06
Add to Favorite Get Latest Update

Remote Sensing Image Scene Oriented Convolutional Neural Network Recursive Recognition Model

He Haiqing;Pang Yan;Chen Xiaoyong;School of Geomatics,East China University of Technology;Key Laboratory of Watershed Ecology and Geographical Environment Monitoring,NASG;School of Resource and Environmental Sciences,Wuhan University;  
In order to solve low separability and rough details in scene recognition,remote sensing image scene oriented convolutional neural network recursive recognition model is presented.Firstly,deep convolutional neural network with multi-convolutional layers and multi-pooling layers is constructed by multi-resolution scenes.Then quad-grids are subdivided to DCNN scene recursive recognition based on Confusion Index(CI)by softmax probability,and multi-sliding windows are used to tune recursively for accurately locating scene targets.Experimental results show that the proposed model can adapt scene recognition with different scale,and significantly improve the accuracy compared with the commonly used DCNN.
【Fund】: 国家自然科学基金项目(41401526);; 江西省自然科学基金项目(20171BAB213025);; 流域生态与地理环境监测国家测绘地理信息局重点实验室资助课题(WE2015003);; 江西省教育厅科技项目;; 江西省高等学校科技落地计划项目(KJLD14049)
【CateGory Index】: TP183;TP751
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved