天津师范大学学报（自然科学版）2017，Vol.37Issue(5)：50-54,5.
基于堆叠去噪自编码器算法的穿墙人体检测
Through wall human detection based on stacked denoising autoencoder algorithm
摘要
Abstract
The application of ultra-wideband radar in the detection of through wall human has been more mature.The algorithm of stacked denoising autoencoder (SDAE) is applied to identify and classify the through wall human status.The unsupervised learning method is used to train the autoencoder network in order to obtain more abstract feature of the original data,then a classifier is added at the end of the network.The supervised learning method is used to fine-tuning the network to get the optimization of the model.At last,set data is tested into the network model for testing.Experimental results showed that the stacked denoising autoencoder deep network can effectively classify and identify the through wall human status.关键词
超宽带/堆叠去噪自编码器/分类器Key words
ultra-wideband/stacked denoising autoencoder/classifier分类
信息技术与安全科学引用本文复制引用
王为,蒋羽,王丹..基于堆叠去噪自编码器算法的穿墙人体检测[J].天津师范大学学报（自然科学版）,2017,37(5):50-54,5.基金项目
Supported by National Natural Science Foundation of China(61271411),Natural Youth Science Foundation of China(61501326),Tianjin Research Program of Application Foundation and Advanced Technology (15JCZDJC31500) and Tianjin Science Foundation (16JCYBJC16500). （61271411）
