分类阶段 meaning in Chinese
classification stage
sort phase
sorting phase
Examples
- Furthermore , it is necessary to enhance robust and precision for vision sysem . in the practical section , three pixel labling algorithms are introduced , i . e . invariable threshold method , adaptive threshold method , and statistical model method
在视觉系统的设计实现过程中，本文提出了将恒定阈值方法、自适应阈值方法，以及统计模型方法应用于系统的象素分类阶段。 - On the view of customization theory , the method of information processing for customization is summarized : quality function development and product function architecture , then the need function development ( nfd ) as the design way of implementing sub - system of customization information dealing is proposed based on them . the configuration include three parts : transmission function , need function and developing function . the adapting four steps for implementing are proposed : the collection and classification stage of customization information , the analysis stage of customization information , matching stage and evaluating stage for producing
尤其是从mc个性化理论出发，总结前人个性化信息处理方法：质量功能配置法和产品族构建法的基础上，提出基于树形的两极需求功能配置法的框架：传导函数、需求函西安理工大学硕士学位论文数、配置函数，作为个性化信息处理子系统的设计思路，并详细阐明了该方法的四个实施步骤：个性化信息收集和分类阶段、个性化需求分析阶段、个性化需求信息配置阶段、可制造性评价阶段，指明了各个阶段的方法在个性化信息处理子系统中的应用，为个性化信息处理于系统的实现奠定了基础。 - In the pre - processing phase , each character is fed into a pre - processor , this makes feature extraction and recognition easy . in the first - grade classification phase , the dissertation puts forward border - table subtract of maximum and minimum feature left - border - table intermission feature improving width feature crossing amount average feature , these features combines with some existing features , realizes the ability of classification in the first - grade classification phase better
在第一级分类阶段，本文提出了边沿表极值差特征、左边沿表间断特征、改进的宽度特征、针对所区分的字符在不同局部范围取交截特征的平均值与阈值比较等特征，这些特征与已有的一些特征相结合，较好的实现了在第一级分类阶段对字符的分类能力。 - This dissertation brings forward and realizes the multilevel classifiable method which is based on characters coding . above all , this method realizes the first - grade classification by extracting enough effective characters from characters and coding them , to the others which coundn " t be recognized by the first - grade classification , the method will adopt the second - grade classification using template matching to recognize these characters
本文提出并实现了基于特征编码的多级分类识别方法，通过给字符抽取足够多的有效的特征并给特征编码实现第一级分类，对于第一级分类后仍不能区分的字符，再进入第二级分类用模板匹配的方法最终达到区分的目的，这种方法的重点在第一级分类阶段。