分类识别,classification and recognition
1)classification and recognition分类识别
1.Structural design ofclassification and recognition expert system for soil remote sensing;土壤遥感分类识别专家系统的结构设计
2.Feature-based fuzzy-neural network approach for targetclassification and recognition in remote sensing images基于特征的模糊神经网络遥感图像目标分类识别
3.Aiming at the existing problems in pattern recognition of surface defect images of cold strips,aclassification and recognition method is proposed to solve them,based on improved support vector machine(SVM).针对冷轧带钢表面缺陷图像模式识别中存在的问题,提出了基于改进支持向量机的冷轧带钢典型表面缺陷分类识别方法。
英文短句/例句
1.The Research of Intelligence Algorithm for the Classification of SAR Sea Ice Images;SAR海冰图像智能分类识别算法的研究
2.The Study of Classification and Indentification Based on Ground-Objects Spectra Database;基于地物波谱数据库的分类识别研究
3.Research on Modulation Classification and Recognition Algorithm of Communication Signals;通信信号调制方式分类识别算法研究
4.Classification between rectangular and ellipsoid/circular areas矩形和(椭)圆区域目标的分类识别
5.Application of S-transform to feature extraction and classification of underwater targetS变换在水下目标分类识别中的应用
6.The drive you specified has an unrecognized partition type.指定的驱动器有无法识别的分区类别。
7.A unit used for classification and discrimination in pattern recognition.在模式识别中，用于分类和判别的装置。
8.Topology Recognition by Profile-HMM Based on a Novel Classification and Structure-Alignment;蛋白质折叠类型分类及其Profile HMM识别
9.A Method of Stroke Classification and Recognition in On line Handwritten Chinese Character Recognition联机手写体汉字识别中的笔划分类及笔划识别
10.The Sole Texture s Automatic Identification and Classification Based on the Pattern Identification;基于模式识别的鞋底花纹自动识别与分类
11.Application of the Clustering Analysis in the Large Vocabulary Chinese Character Recognition;聚类分析及其在大类别汉字识别中的应用
12.Recognition and Classification of Metal Fracture Surface Models Using Fractal应用分形进行金属断口的识别分类
13.The Category Assistant learns how to recognize categories by examining existing categorized documents.分类助手通过检查现有已分类的文档了解如何识别类别。
14.The main research work in this paper as follow:①Divide Go Knowledge into distinct catalogs, and treat them respectively.①将围棋中的知识划分不同的类别，分别对待。
15.Study on Phrase Classifier in Chinese Character Recognition汉字识别中以词为分类单位的分类器研究
16.A FCM-PNN Classifier for Speaker Recognition基于FCM-PNN分类器的说话人识别
17.Chin Contours Classification for Face Recognition用于人脸识别的下颌轮廓线分类方法
18.A on-line stroke based multi-level handwriting Chinese character recognition method识别联机手写体汉字的多级分类方法
相关短句/例句
classification[英][,kl?s?f?"ke??n][美]["kl?s?f?"ke??n]分类识别
1.Support Vector Machine(SVM),a kind of machine learning method,can efficiently solve theclassification problem.提出了一种用于最佳特征子集选取的特征筛选算法,且实现了特征与分类识别相关性强度的排序,并通过使用该算法对Ⅱ型糖尿病判别与风险因素筛选,求证了该方法的可靠性和可行性。
2.Generally, gait recognition consists of three parts: processing gait sequence, feature extraction and featureclassification.步态识别主要包括步态图像预处理、步态特征提取和步态分类识别三个部分。
3.Feature extraction andclassification of under-water target are the points of the study .研究工作的重点是水下目标信号的特征提取及分类识别，深入研究能够有效提取水下目标特征的特征提取方法及有效分类器的设计方法。
3)classification recognition分类识别
1.Six typical radar emitter signals are chosen to be made the experiment of Holder feature extraction andclassification recognition.文中选择了6种典型的雷达辐射源信号进行特征提取和分类识别实验。
4)classified recognition分类识别
5)Classification and identification分类识别
6)identification and classification识别分类
1.Secondly,pivotal technologies are elaborated,according to three main steps of gait recognition,namely,pretreatment of gait sequence image,gait feature extraction and gaitidentification and classification.首先,给出了步态识别的特点;其次,根据步态序列图像的预处理、特征处理和识别分类三个阶段,阐述了目前所采用的主要技术及各种技术的主要优缺点;最后,提出了步态识别的应用前景和目前存在的主要问题。
延伸阅读
汉字分类识别汉字分类识别Chinese character recognition by classificationhQnzi fsnlei ShibiG汉字分类识别(Chi~ch~ter八叉邺，itionby cl别洛ifiCation】根据某种判别准则，用统计或结构的方法，把汉字模式多维特征向量(参见汉宇识别鑫本方法)构成的特征空间划分为若干子空间的过程。由于汉字数量巨大，汉字模式样本甚多，为提高识别速度，汉字识别通常采用两到三级分类识别方案。其中最后一级分类(通过该分类就识别出汉字)称为细分类，前面若干级分类都称为粗分类。汉字识别分类方法的选择原则是:①分类特性好。即类内各样本距离小，类间距离大，各类重叠样本少。②分类稳定性好，抗干扰能力强。③粗分类的正确分类率和稳定性应比细分类高。④每类汉字的相关性要小，分类速度快。⑤分类特征易提取，简单，维数低。⑥粗分类要和细分类相协调。以上要求很难同时满足，分类(特别是粗分类)的稳定性和正确分类率是首先需要考虑的。分类方法有重叠区分类、中心提取分类、判定树分类、引导树分类等。在汉字分类时，用某种类似度(或距离)准则，把未知文字特征和字典中标准文字特征逐一比较，按相似性从大到小排序，取i位以前(包括第i位)的所有文字为一类，所得到的正确分类的文字占全部需要识别文字的百分比，称为累计分类率。第i位的累计分类率就是从第1位到第i位所得正确分类字数占全部需要识别文字的百分比。第1位的累计分类率就是识别率，第。位(n为全部需要识别文字数)累计分类率总是100%。
