【摘 要】
：
With the development of social informatization technology,the problems of individual information security are becoming serious.Now-adays identity identification has been required essentially in govern
【机 构】
：
School of Information Science and Technology,Northwest University,China
【出 处】
：
第六届中国计算机学会大数据学术会议
论文部分内容阅读
With the development of social informatization technology,the problems of individual information security are becoming serious.Now-adays identity identification has been required essentially in government and business field.In this paper,we summarize and analyze the identifica-tion principles and identification methods based on biometrics,including the present researches fingerprint,palmprint,iris,human face,vein,gait and signature,and make comparative analysis of the differences of the error recognition rate,stability,acquisition difficulty and counterfeiting degree.Finally,the prospects of biometric recognition technologies are discussed additionally.
其他文献
随着智能电视的普及,节目付费成为电视生产企业或视频内容企业最重要的利润来源之一.挖掘潜在付费用户,促使用户付费购买增值服务越来越成为企业亟待解决的问题.本文首先基于国内最大的电视厂家之一的海信公司日志数据的特点,提出了对日志信息扩展、特征衍生以及特征提取的解决方案.结合深度模型在高阶抽象特征学习上的优势以及线性模型在低阶特征学习上的优势,提出了Simplified Wide&Deep(SWD)模型
Weather classification is getting more and more attractive because it has many potential applications,such as visual systems and intelligent transportation,especially in transportation.However,the res
蛋白质二级结构预测是生物信息学上的一个关键问题.近年来,由于深度学习的成功,本文将深度学习应用到这一问题上面,设计了一种多方面的自注意力机制的深度卷积循环网络(Multi-Aspect Self-Attentive Network,MASAN)来进行蛋白质二级结构的预测.首先,本文使用了CNN来处理氨基酸序列,提取氨基酸序列的局部特征;在此基础上,利用双向循环神经网络(Bi-GRU)处理整个氨基酸
Big data computing and analysis can uncover hidden patterns,correlations and other insights by examining large amounts of data.Comparing with the traditional processor,the new types of processors,just
为了高效地从海量的水文传感器数据中检测出异常值,提出了一种基于SparkR的水文时间序列异常检测方法.对数据进行清洗后,采用滑动窗口配合自回归积分滑动平均模型在SparkR平台上进行预测,然后对预测的结果计算置信区间,在区间范围以外的,将其判定为异常值.基于检测结果,利用K均值算法对原数据进行聚类,同时计算其状态转移概率,对检测出的异常值进行质量评估.以在滁河获取的水文传感器数据为实验数据,分别在
Research on pollution localization using sensor monitoring networks has important significance for environmental protection.There are some challenges in the detection and localization of water polluti
In the real-world many complex systems exist in the form of heterogeneous networks.As we all know,heterogeneous networks consist of various types of vertices and relations,so it is difficult to deal d
基于语义抽取的机器阅读理解是目前人工智能与大数据相结合的热点应用之一。针对复杂多文本机器阅读理解任务中的语义理解与答案提取问题，提出一种结合外部知识的动态多层次语义理解与答案抽取模型。首先，利用改进的门控单元循环神经网络匹配文本内容与问题集；然后，分别在向量化文本内容及问题集上实施多维度动态双向注意力机制分析，提高语义匹配精度；接着，利用动态指针网络确定问题答案范围，改进网络模型语义匹配效率，降低
Caricature face recognition is an interesting but also a hard task for studying owing to the huge exaggeration between two quite different face modalities,photos and caricatures.So,we propose a new re
头脑风暴优化(Brain Storm Optimization,BSO)算法是一种新型的群体智能优化算法,启发于众人集思广益求解问题的模式,适合求解复杂多峰函数优化问题.但BSO求解多峰极值时需进行重复的迭代运算,面对大规模数据集时会出现计算效率与求解精度过低的现象.为解决上述问题,本文设计并实现了一种基于Spark的并行化头脑风暴优化算法,通过将BSO算法中计算复杂度最高的聚类与新解产生过程并行