人脸识别实质是稀疏超高维空间、典型的小样本模式识别问题。
Face recognition is essentially a typical small-sample pattern recognition problem in sparse hyper-high dimensional space.
这里是在批处理模式中运行样本代码的步骤。
Here are the steps for running the sample code in batch mode.
它匹配了用户的声音模式，以记录代表14种不同情感类型的语音样本。
It matches the user's voice patterns to recorded speech samples that represent 14 different emotional categories.
这是本样本假定的操作模式。
但是在现实世界中，使开发人员感到困扰的最常见过程在于要开发一种xml格式样本，以满足合适模式的所有用途。
But in the real world, the most common course for harassed developers is to develop a sample of the XML format to serve all purposes of a proper schema.
媒体世界已经从广告支持的免费内容向免费增值模式转变：用免费的样本为付费服务做营销，重点在于附加收费部分。
In the media world, this has taken the form of a shift from ad-supported free content to freemium - free samples as marketing for paid services - with an emphasis on the "premium" part.
样本抽取了由模式来解决问题的最佳解决方案，并且由具有技能的开发人员创建。
The exemplar represents the best solution to the problem solved by the pattern and will be created by a skilled developer.
在分析样本的时候，JET简化了创建模式的过程，并且让所有人都能够学习使用。
In analyzing the exemplar, JET simplifies the pattern creation process and makes this capability something that anyone can learn to use.
在附录A中重现了完整的模式，而在附录B中重现了样本配置文件。
The complete schema is reproduced in Appendix a, while a sample configuration file is reproduced in Appendix B.
传统上，支持JMX包括用样本代码实现模式。
Traditionally, supporting JMX involves implementing patterns with boilerplate code.
为了提供实现，我设计了一个应用Web服务体系结构的MVC模式样本。
To provide an implementation, I have designed a sample MVC pattern with a web service architecture applied to it.
附件中样本项目的Basic . jsp页面论证了自动操作和手动操作模式中的ProgressBar组件。
The Basic.jsp page in the attached sample project demonstrates the ProgressBar component in both automatic and manual modes.
使用Examplotron从这些样本文档生成用于生产的RELAX NG模式，这使我省掉了大概一百多个小时的工作量，从而为客户节省了好几万美元。
Using Examplotron to generate the production RELAX ng schemata from these sample documents saved me perhaps over a hundred hours of effort, and thus saved them tens of thousands of dollars.
如果您感兴趣，可以将sample. appdef从样本项目中复制到模式项目，并覆盖缺省的项目。
For fun, copy the sample.appdef from the exemplar project into the pattern project and override the default project.
当然，作为Examplotron模式提供的样本xml不可能表达验证所必需的所有信息。
Of course, the sample XML I've presented as an Examplotron schema probably doesn't convey all the information required for validation.
看一下图11中的样本portlet，它使用这个设计模式和WebSpherePortal的普及api。
Look at the sample portlet in Figure 11, which USES this design scheme and the WebSphere Portal pervasive APIs.
在开始这项工作前，我们将向您介绍一个示例样本(在后续的文章中，我们将讨论一些工具，这些工具可以用来对样本进行分析，以便生成模式本身)。
To begin, then, we will show you a sample exemplar (in later articles, we will discuss tools that can actually be used to analyze your exemplar in order to generate the pattern itself.)
与使用JSPand servlet样本一样，在从应用程序服务器获取连接工厂时，EJB运行于受管模式下。
As with the JSP and servlet sample, the EJB runs in managed mode when the connection factory is obtained from the application server.
样本3给出了ServiceLocator接口的例子，并且样本6给出了ServiceLocator模式的实现，这个实现可以用来确定AccountEJB的版本1。
Sample 3 shows a ServiceLocator interface example, and Sample 6 shows an implementation of the ServiceLocator pattern which can be used to locate version 1 of the Account EJB.
您可能还记得，在我们的数据库模式中(参见“样本数据库”小节)，我们将那些XML文档存储在“clients”表的“contactinfo”列中。
As you might recall from our database schema (see "Sample database" section), XML documents are stored in the Contactinfo column of the Clients table.
作者使用比例训练的BP算法，提出对训练模式进行样本重组的方法，其特点是训练速度快、特征抽取能力强。
A scale training algorithm of BP neural network is used, and sample reorganization method is proposed. Its advantage is the fast training speed and good feature extraction ability.
将人脸模式的多个样本作为子模式，并将较多的人脸模式部分相交地分组，以减小计算量和便于识别系统的扩展。
A method taking multi samples as sub modes and grouping face modes into partial intersection ones was proposed to reduce computation and improve system extension property.
通过不同组织来源的样本质谱图的比较，鉴别出共同的表达模式。
Spectra from different tissue samples can be compared and common patterns of expression identified.
均值移位算法是一种搜索与样本点分布最相近模式的非参数统计方法。
The mean shift algorithm is a nonparametric statistical method for seeking the nearest mode of a point sample distribution.
支持向量机是一种基于统计理论的机器学习算法，在解决小样本、非线性及高维模式识别中有独特的优势。
Support vector machine is a kind of machine study algorithm based on statistic theory, it has special advantage in solving small sample, non-linear and high dimension mode recognition.
对于这样一个高维数、非线性的小样本问题，许多传统的模式识别方法都容易出现过学习或欠学习现象。
When solving this small sample problem with high dimension and nonlinear, many traditional pattern recognition methods will tend to occur overfitting phenomenon.
数学模型采用一个简单而实用的无标准样本学习模式识别方法。
Mathematic model is a simple and practical model recognition without standard sample studying.
单个临床样本也会产生数以千计的描述蛋白表达模式的数据。
A single clinical tissue sample could generate many thousands of data points describing protein expression patterns.
介绍了BP网络的基本原理，研究了基于神经网络的故障诊断方法，建立了风机常见故障模式样本。
The basic principle of BP network is introduced, the trouble diagnosis method based on neural network is researched. An usual trouble mode sample book for fan is established.
介绍了BP网络的基本原理，研究了基于神经网络的故障诊断方法，建立了风机常见故障模式样本。
The basic principle of BP network is introduced, the trouble diagnosis method based on neural network is researched. An usual trouble mode sample book for fan is established.
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