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浏览/检索结果: 共3条，第1-3条 帮助 限定条件 专题：长春光学精密机械与物理研究所    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Global random graph convolution network for hyperspectral image classification 期刊论文 Remote Sensing, 2021, 卷号: 13, 期号: 12 作者:  C. Zhang;  J. Wang and K. Yao 收藏  |  浏览/下载：2/0  |  提交时间：2022/06/13 Capsule graph neural network based on global and local features fusion 期刊论文 Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2021, 卷号: 51, 期号: 3, 页码: 1048-1054 作者:  R. Qian;  R. Zhang;  K.-J. Zhang;  X. Jin;  S.-L. Ge and S. Jiang 收藏  |  浏览/下载：2/0  |  提交时间：2022/06/13 A method of aircraft image target recognition based on modified PCA features and SVM (EI CONFERENCE) 会议论文 9th International Conference on Electronic Measurement and Instruments, ICEMI 2009, August 16, 2009 - August 19, 2009, Beijing, China Donghe W.; Xin H.; Wei Z.; Huilong Y. 收藏  |  浏览/下载：21/0  |  提交时间：2013/03/25 Automatic target recognition(ATR) is an important task in image application. This paper concentrates on two key subroutines of ATR system: Dimensionality reduction and Classifier. After pretreatment on original features a self-organizing neural network trained with the Hebbian rule is used to extract the principal component features. Then a classifier based on Directed Acyclic Graph Support Vector Machines(DAGSVM) is adopted to recognize more than two types of aircraft targets. The experiment results show the proposed method achieves better subset features and higher recognition rate. 2009 IEEE.