期刊文献+
共找到3篇文章
< 1 >
每页显示 20 50 100
Method to generate training samples for neural network used in target recognition
1
作者 何灏 罗庆生 +2 位作者 罗霄 徐如强 李钢 《Journal of Beijing Institute of Technology》 EI CAS 2012年第3期400-407,共8页
Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new meth... Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new method based on virtual model and invariant moments was proposed to generate training samples.The method was composed of the following steps:use computer and simulation software to build target object's virtual model and then simulate the environment,light condition,camera parameter,etc.;rotate the model by spin and nutation of inclination to get the image sequence by virtual camera;preprocess each image and transfer them into binary image;calculate the invariant moments for each image and get a vectors' sequence.The vectors' sequence which was proved to be complete became the training samples together with the target outputs.The simulated results showed that the proposed method could be used to recognize the real targets and improve the accuracy of target recognition effectively when the sampling interval was short enough and the circumstance simulation was close enough. 展开更多
关键词 pattern recognition training samples for neural network model emulation space coordinate transform invariant moments
下载PDF
Design and Implementation of Verification Code Identification Based on Anisotropic Heat Kernel 被引量:2
2
作者 LIU Lizhao LIU Jian +3 位作者 DAI Yaomei XU Huarong YIN Huayi ZHU Shunzhi 《China Communications》 SCIE CSCD 2016年第1期100-112,共13页
Many websites use verification codes to prevent users from using the machine automatically to register,login,malicious vote or irrigate but it brought great burden to the enterprises involved in internet marketing as ... Many websites use verification codes to prevent users from using the machine automatically to register,login,malicious vote or irrigate but it brought great burden to the enterprises involved in internet marketing as entering the verification code manually.Improving the verification code security system needs the identification method as the corresponding testing system.We propose an anisotropic heat kernel equation group which can generate a heat source scale space during the kernel evolution based on infinite heat source axiom,design a multi-step anisotropic verification code identification algorithm which includes core procedure of building anisotropic heat kernel,settingwave energy information parameters,combing outverification codccharacters and corresponding peripheral procedure of gray scaling,binarizing,denoising,normalizing,segmenting and identifying,give out the detail criterion and parameter set.Actual test show the anisotropic heat kernel identification algorithm can be used on many kinds of verification code including text characters,mathematical,Chinese,voice,3D,programming,video,advertising,it has a higher rate of 25%and 50%than neural network and context matching algorithm separately for Yahoo site,49%and 60%for Captcha site,20%and 52%for Baidu site,60%and 65%for 3DTakers site,40%,and 51%.for MDP site. 展开更多
关键词 verification code image recognition data mining scale space anisotropic heat kernel
下载PDF
Multi-view space object recognition and pose estimation based on kernel regression 被引量:1
3
作者 Zhang Haopeng Jiang Zhiguo 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2014年第5期1233-1241,共9页
The application of high-performance imaging sensors in space-based space surveillance systems makes it possible to recognize space objects and estimate their poses using vision-based methods. In this paper, we propose... The application of high-performance imaging sensors in space-based space surveillance systems makes it possible to recognize space objects and estimate their poses using vision-based methods. In this paper, we proposed a kernel regression-based method for joint multi-view space object recognition and pose estimation. We built a new simulated satellite image dataset named BUAA-SID 1.5 to test our method using different image representations. We evaluated our method for recognition-only tasks, pose estimation-only tasks, and joint recognition and pose estimation tasks. Experimental results show that our method outperforms the state-of-the-arts in space object recognition, and can recognize space objects and estimate their poses effectively and robustly against noise and lighting conditions. 展开更多
关键词 Kernel regression Object recognition Pose estimation space objects Vision-based
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部