Parallel design of convolutional neural networks for remote sensing images object recognition based on data-driven array processor  

作　　者：Shan Rui Jiang Lin Deng Junyong Cui Pengfei Zhang Yuting Wu Haoyue Xie Xiaoyan 

机构地区：[1]School of Electronic Engineering,Xi'an University of Posts and Telecommunications,Xi'an 710121,China [2]Laboratory of Integrated Circuit Design,Xi'an University of Science and Technology,Xi'an 710054,China [3]School of Computer Science and Technology,Xi'an University of Posts and Telecommunication,Xi'an 710121,China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2020年第6期87-100,共14页中国邮电高校学报（英文版）

基　　金：This work was supported by the National Natural Science Foundation of China(61802304,61834005,61772417,61634004,61602377);the Shaanxi Provincial Co-ordination Innovation Project of Science and Technology(20I6KTZDGY02-04-02);the Shaanxi Provincial Key Research and Development Plan(2017GY-060).

摘　　要：Object recognition in very high-resolution remote sensing images is a basic problem in the field of aerial and satellite image analysis.With the development of sensor technology and aerospace remote sensing technology,the quality and quantity of remote sensing images are improved.Traditional recognition methods have a certain limitation in describing higher-level features,but object recognition method based on convolutional neural network(CNN)can not only deal with large scale images,but also train features automatically with high efficiency.It is mainly used on object recognition for remote sensing images.In this paper,an AlexNet CNN model is trained using 2100 remote sensing images,and correction rate can reach 97.6%after 2000 iterations.Then based on trained model,a parallel design of CNN for remote sensing images object recognition based on data-driven array processor(DDAP)is proposed.The consuming cycles are counted.Simultaneously,the proposed architecture is realized on Xilinx V6 development board,and synthesized based on SMIC 130 nm complementary metal oxid semiconductor(CMOS)technology.The experimental results show that the proposed architecture has a certain degree of parallelism to achieve the purpose of accelerating calculations.

关 键 词：convolutional NEURAL networks REMOTE sensing images OBJECT recognition array PROCESSOR DATA-DRIVEN 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置] TP183[自动化与计算机技术—控制科学与工程]