Finding the number of clusters in ordered dissimilarities

As humans, we have innate faculties that allow us to efficiently segment groups of objects. Computers, to some degree, can be programmed with similar categorical capabilities, which stem from exploratory data analysis. Out of the various subsets of data reasoning, clustering provides insight into the structure and relationships of input samples situated in a number of distributions. To determine these relationships, many clustering methods rely on one or more human inputs; the most important being the number of distributions, c, to seek. This work investigates a technique for estimating the number of clusters from a general type of data called relational data. Several numerical examples are presented to illustrate the effectiveness of the proposed method.     

人脸检测方法综述

人脸检测问题的提出是为了在自动人脸识别系统中的定位,近年来,由于其在安全控制、人机界面、视觉监测、基于内容的检索等领域的应用价值,开始作为一个独立的课题受到研究者的普遍重视。该文从人脸检测的模式、人脸特征的提取、人脸特征的综合、评估标准等角度,系统阐述了人脸检测系统,并将人脸检测方法分为：基于几何特征的方法,基于肤色模型的方法和基于统计理论的方法,并对各个方法的优缺点进行了比较,最后,对人脸检测今后的发展方向进行了探讨。     

Generating relational database transactions from eb 3 attribute definitions

eb ³ is a trace-based formal language created for the specification of information systems. In eb ³, each entity and association attribute is independently defined by a recursive function on the valid traces of external events. This paper describes an algorithm that generates, for each external event, a transaction that updates the value of affected attributes in their relational database representation. The benefits are twofold: eb ³ attribute specifications are automatically translated into executable programs, eliminating system design and implementation steps; the construction of information systems is streamlined, because eb ³ specifications are simpler and shorter to write than corresponding traditional specifications, design and implementations. In particular, the paper shows that simple eb ³ constructs can replace complex SQL queries which are typically difficult to write.

基于局部二值模式和级联AdaBoost的多模态人脸识别

提出了一种基于局部二值模式(LBP)和 级联AdaBoost的多模态人脸识别方法。采用级联AdaBoost算法分别从人脸深度图像和灰度图像的大量区域LBP直方图(RLBPH)中选出最有利于分类的少量特征,并连接成一个直方图向量,再分别用线性判别分析构建相应的线性子空间,用余弦相似度作为投影向量的相似度量,用求和规则进行信息融合。在FRGC数据库上的实验结果表明,提出的方法采用少量的特征取得了很好的识别效果,等错误率仅为1.40%。     

基于小波变换与神经网络的表面肌电信号的情感识别

情感识别是情感计算的一个关键问题。针对表面肌电图(EMG)的非平稳性,采用小波变换方法对表面肌电信号进行分析,提取小波系数最大值和最小值构造特征矢量,分别输入用L-M算法改进的BP神经网络分类器和最近邻法分类器进行情感识别。实验表明,提取EMG的小波系数对joy、anger、sadness、pleasure四种情感进行识别,BP神经网络分类器识别效果优于最近邻法分类器。说明小波变换的方法对EMG进行分析是可行且有效的,并有很大的应用前景。     

基于J2EE的地税网上申报系统的设计与实现

文章阐述了地税网上申报系统开发的背景和意义;介绍了基于J2EE的网上报税系统的结构、软件的主要功能及具体的实现方法和所用的关键技术;总结了所用技术的优势以及系统中难点的处理。     

基于模板匹配的联机手写数字识别

在深入学习和研究模板匹配分类理论和模式识别的过程基础上.利用模板匹配分类算法设计了一个图像分类器.该分类器通过对待分类样本与训练集中的样本之间距离的计算.对0～9这十类联机手写数字图像进行分类识别.     

一种基于模板匹配的数字仪表字符识别方法

针对工业生产中数字式仪表的自动识别问题,利用图像处理技术和匹配技术,提出了一种仪表显示字符的识别方法.通过图像灰度化、直方图增强和中值滤波去噪等技术对图像进行预处理.运用相关匹配图形模板匹配的方法对输入的字符模式进行初始分类和识别.测试结果表明,算法能够自动、快速、准确地识别出仪表的显示字符.     

汽车牌照定位算法研究

车牌定位是牌照自动识别系统中最为关键的环节,也是栓验牌照自动识别系统优劣的重要技术指标.通过对近年来众多学者、专家提出的新方法、新思路进行探讨和研究,结合国内汽车牌照的纹理特点,进行全面、深入的剖析,旨在探求通用的定位算法.     

Point Set pattern matching ind-dimensions

In this paper we apply computational geometry techniques to obtain an efficient algorithm for the following point set pattern matching problem. Given a setS ofn points and a setP ofk points in thed-dimensional Euclidean space, determine whetherP matches anyk-subset ofS, where a match can be any similarity, i.e., the setP is allowed to undergo translation, rotation, reflection, and global scaling. Motivated by the need to traverse the sets in an orderly fashion to shun exponential complexity, we circumvent the lack of a total order for points in high-dimensional spaces by using an extension of one-dimensional sorting to higher dimensions (which we call circular sorting). This mechanism enables us to achieve the orderly traversal we sought. An optimal algorithm (in time and space) is described for performing circular sorting in arbitrary dimensions. The time complexity of the resulting algorithm for point set pattern matching is O(n logn+kn) for dimension one and O(kn^d) for dimensiond2.Supported in part by CNPq-Conselho Nacional de Desenvolvimento Cientifico e Tecnológico (Brazil) under Grants 200331/79, 300157/90-8, and 500787/91-3.Supported in part by the National Science Foundation under Grant CCR 8901815.