casia
- n.卡西亚
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Experiment on gait database of CASIA is used to analysis and verify the key technologies put forward in the paper .
在中国科学院自动化研究所提供的CASIA步态数据库上,对本文提出的关键技术进行实验分析与验证。
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Good recognition results are achieved after 40000 recognition experiments have been done in the CASIA iris database ( version 1.0 ) .
论文的最后对本文的虹膜识别算法在CASIA虹膜数据库(version1.0)中进行了40000次的虹膜识别实验,并得出了较好的识别效果。
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In the CASIA ( B ) gait database , the recognition accuracy of 99.46 % was acquired .
在CASIA(B)步态数据库上获得99.46%的识别精度。
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Experimental results on the CASIA iris database images show that the proposed segmentation method can decrease the Equal Error Rate of the recognition system from 8 % to 4.4 % .
在CASIA图像库上的实验结果表明该方法可将系统识别等错误率从8%降低到4.4%。
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This paper shows how to make use of computers to facilitate sampling inspection based on GB2828-87 and ISO2859 . A computer program CASIA is introduced .
本文以计数调整型抽样检查标准GB2828-87和ISO2859为例,说明了如何利用计算机辅助质量抽样检查,并介绍了笔者编制的计算机软件CASIA系统。
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Because of the particularity of gait recognition , we design an immune model which can work effectively based on theory analysis and experiments on CASIA base using the selected characteristics of this paper .
针对步态识别领域的特殊性,在理论分析和大量实验的基础上设计提出了一个较为有效的人工免疫系统,采用本文选用的步态特征对中科院CASIA步态图像数据库进行训练、识别。
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To process an iris image , this system needs only 0.2 second . The EER ( Equal Error Rate ) is 3.9 % in testing the CASIA iris library .
其中,本系统对一枚虹膜进行处理的速度小于0.2秒,在CASIA虹膜数据库上测试的EER(等错误概率)为3.9%。
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The thesis designs the simulation experiment on the CASIA gait database . The experimental results demonstrate that the recognition has been good improvement after fusion and is much better than those based on single feature .
设计了在CASIA步态数据库上的仿真实验,实验表明,静态特征和动态特征融合后的性能优于基于单个特征步态识别算法,且识别率有了较好的改善。
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Simulation results on CASIA database show that the recognition rate of this method is 95 % , and obviously higher than the recognition method of only using single feature , it shows that this is an effective identification method .
CASIA数据库上的仿真结果表明,本方法的识别率达到90%,明显高于基于单一特征的识别方法,说明这是一种有效的识别方法。
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Last reference templates are built and gait patterns are classified based on weighted dynamic time warping matching . Test on CASIA gait Lib . shows that the correction of classification reaches on 90 % .
步态的分类采用改进后的动态时间扭曲(DTW)方法进行动态模板匹配,基于CASIA步态库的测试表明,该方法的分类准确率达90%。
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The experiments implemented on CASIA iris database V1.0 show that , the system performs very well , with a success rate of 96.6 % in location and the equal error rate of 0.23 % in recognition .
整个虹膜识别系统在中科院虹膜数据库上,取得了96.6%的定位正确率和0.23%的识别等错率。
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The experiments of the proposed algorithm has been compared among other implemented algorithms on the CASIA iris image database , and the experiment results demonstrated that the proposed algorithm has the fastest speed than other algorithms while ensure the locating accuracy .
本文对该算法进行了实验,并与其他现有的定位算法同在CASIA虹膜图像库上进行比较,实验结果表明本文提出的算法在保证准确率的基础上具有比其他几种算法更快的速度。