用于多姿态人耳识别的局部线性嵌入及其改进算法

通过分析目前人耳识别所采用的各种主要方法,将流形学习局部线性嵌入(LLE)算法用于多姿态人耳识别,并针对LLE算法存在的局限提出一种改进LLE算法.改进后的LLE算法依据Hsim距离选择邻域,较好地避免了高维空间中邻域点选取的不稳定性.实验结果表明,利用LLE解决多姿态人耳识别问题是可行的而且具有较明显的优势.用改进LLE算法进行多姿态人耳识别能够获得更高的识别率,验证了算法改进的有效性.     

基于彩色人脸图像的信息融合与识别方法

图像的彩色信息进行图像识别并有效地降低因利用颜色信息所带来的计算量大幅增加问题,提出了一种基于彩色图像的监督近邻保留嵌套的人脸识别方法,通过对图像的彩色信息进行信息融合并利用监督近邻保留嵌套算法来提高人脸识别的效率。首先,采用Gabor变换分别对彩色图像的每个彩色分量图提取Gabor特征;然后采用典型相关分析对所提取的Gabor特征进行特征融合,并采用监督近邻保留嵌套算法对高维彩色图像特征进行降维;最后,采用最近邻分类器对图像进行分类。实验基于XM2VTS和FRAV2D彩色人脸数据库,采用主成分分析、线性判别分析以及监督近邻保留嵌套对基于灰度图像的Gabor特征和基于彩色信息融合的Gabor特征进行降维,其结果说明多信通彩色图像融合技术与监督近邻保留嵌套结合的方法可以显著提高识别系统性能。     

结合Gabor小波和监督保局投影的人耳识别

针对人耳识别中人耳的角度变化这个难点问题,提出一种结合Gabor小波和监督保局投影的人耳识别算法.由于Gabor特征维数高、冗余大,首先通过统计样本的边缘点再采样的方法对人耳进行稀疏的描述,然后利用类别可分离性判据评价Gabor展开系数的分类能力,选择最有利于识别的Gabor展开系数构造新的Gabor特征.在人耳库中的实验结果表明,采用文中算法提取的Gabor特征维数少、鉴别能力强,结合监督保局投影进行识别取得了很高的识别率,对于人耳角度的变化具有良好的鲁棒性.     

人耳和侧面人脸融合的多模态身份识别

首先分别对人耳和侧面人脸建立基于全空间线性判别分析(FSLDA)的分类器;然后采用贝叶斯决策理论中常见的积、和、中值多分类器融合算法,并对投票算法进行了改进.实验结果表明,与单一的人耳或侧面人脸特征识别比较,人耳和侧面人脸融合的多模态识别率得到提高,并扩大了识别范围.     

基于局部线性嵌入和最近特征线的人耳识别

针对人耳生物特征,通过分析早期人耳识别方法的不足,提出了一种局部线性嵌入（LLE）和最近特征线（NFL）相结合的人耳识别方法。首先依据流形学习思想,采用局部线性嵌入算法提取人耳图像特征,然后采用最近特征线分类器进行人耳识别。实验结果表明,该方法在人耳姿态变化时能够取得非常理想的识别率,提高了人耳识别的鲁棒性,增强了人耳识别技术的实用性。     

基于Gabor+PCA特征与粒子群算法的部分遮挡人耳识别研究

在分析人耳Gabor特征基础上,提出一种主成分分析降维并利用基于粒子群优化训练的人工神经网络对部分遮挡人耳进行识别方法。选取了PCA方法降维后人耳图像的Gabor特征值作为人工神经网络训练样本,利用粒子群优化算法与多层前馈网络结合算法训练神经网络。与多种方法对比的实验表明,针对部分遮挡人耳的测试实验,基于Gabor+PCA特征与粒子群算法的部分遮挡人耳识别方法具有高识别性能,取得好的效果。     

基于Gabor和改进LDA的人耳识别

针对人耳识别中无法避免的小样本问题,提出了基于Gabor特征和改进LDA(ILDA)的识别算法。该算法首先提取人耳局部Gabor特征,然后重新定义Fisher准则和类内分散度矩阵,再将高维空间映射到低维后寻找最优投影方向,最后利用训练样本与测试样本特征投影值的欧氏距离进行分类识别。与传统方法相比,新算法能有效解决人耳识别中的小样本问题,获得较高的识别准确率。     

多姿态人耳识别的局部线性嵌入及其改进算法

为了提高多姿态人耳识别的准确性,提出了一种改进局部线性嵌入算法的多姿态人耳识别方法。通过曲波变换提取人耳特征,采用改进局部线性嵌入算法对特征进行降维,选择最有利于人耳识别的特征向量;采用RBF神经网络建立人耳分类器实现人耳识别,并采用USTB人耳图像库进行仿真实验。相对于其他方法,该方法获得了更高的人耳识别率,从而验证了算法的有效性。     

基于Gabor小波和局部线性嵌入的人脸识别

提出了一种新的人脸识别算法。该算法采用Gabor小波和一种新颖的方式来提取人脸特征,利用局部线性嵌入（Locally Linear Embedding,LLE）算法来实现数据的非线性降维处理,最后训练基于欧式距离的最近邻分类器进行分类判决。在ORL人脸库中与PCA方法、Gabor小波+PCA方法和直接的LLE算法进行了实验比较,实验结果表明,提出的Gabor小波+LLE的方法具有更优的性能。     

改进的LLE算法在图像分类中的应用

局部线性嵌入算法LLE(Locally Linear Embedding)可以有效地对图像的高维特征进行降维。针对处理样本分布不均匀及近邻因子选择时会出现的问题,在对高维数据降维时,近邻点的选择采用计算测地线距离而非传统的局部欧式距离,且近邻点的个数选择进行预先优化以达到更好的降维效果。实验表明,改进后的LLE算法具有更好的分类精确度,在图像分类过程中比单纯的LLE算法具有更好的分类性能。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.