合成孔径雷达图像的分类方法研究仿真

合成孔径雷达有多个通道,采集得到的远程雷达图象特征较多,图像合成后由于特征的不一致,造成图像维度很高.传统的图像分类方法在设置训练器时,一旦雷达图像特征维数很高,会使得传统的分类器难以训练至给定要求,模型的分类中心发生偏移,造成图像分类不准.提出了一种遗传因子优化的超高维度合成孔径雷达图像分类算法.利用遗传因子优化方法,对采集的雷达图像分类参数进行优化训练,从而获取最优参数.利用搜索空间划分方法,对采集的雷达图像进行分类处理.实验结果表明,改进的算法进行高精度合成孔径雷达图像分类,能够有效提高分类的准确性,从而为航天技术的发展提供依据.     

基于蚁群优化分类规则挖掘的遥感图像分类研究

蚁群优化算法作为群智能理论的主要算法之一,已经成功应用在众多研究领域的优化问题上,但是在遥感数据处理领域还是一个新的研究课题。蚁群优化具有自组织、合作、通信等智能化优点,对数据无需统计分布参数的先验知识,因此在遥感数据处理领域具有很大的潜在优势。介绍了将蚁群优化分类规则挖掘算法应用到遥感图像分类研究领域的理论与算法流程。并采用北京地区的CBERS遥感数据作为实验数据,通过蚁群优化算法构造分类规则,对选择的遥感数据进行了分类实验,并和最大似然分类方法进行对比,实验结果表明,蚁群优化分类规则挖掘算法为遥感图像的分类提供了一种新方法。     

基于分类蚁群算法的彩色图像自动分类

为提升图像自动分类算法的通用性和鲁棒性,加快算法收敛速度,针对图像分类的特点,对传统蚁群算法进行改进,引入分类蚁群模型。随机蚂蚁识别统计图像类别,构建类别表,确定聚类中心;智能蚂蚁按相应的搜索前进策略进行分类。相比基本蚁群分类算法,该算法可以在较短的时间内完成图像的自动分类。     

基于蚁群优化与独立特征集的遥感图像实时分类算法

为了提高遥感图像的实时分类准确率与效率,提出了一种基于蚁群优化算法与独立特征集的遥感图像集实时分类算法。首先,提取遥感图像的小波域特征与颜色特征,并且组成特征向量;然后,采用蚁群优化算法对特征空间进行优化,独立地选出每个分类的显著特征集,从而降低每个子特征空间的维度;最终,每个分类独立地训练一个极限学习机分类器,从而实现对遥感图像集的分类。基于公开的遥感图像数据集进行了仿真实验,结果显示本算法实现了较高的分类准确率,并且实现了较高的计算效率。     

一种基于Bayesian的图像分类算法

提出了一种基于Bayesian的图像分类算法,该算法首先从原始数字图像出发,通过分析图像的特征分布特点,对图像的局部区域扫描分析,然后抽取目标图像的特征元素,得到其颜色、纹理、形状等特征,最后利用Bayesian分类器来实现图像的快速自动分类.实验结果表明,该算法能够有效提取图像的局部特征,从而快速、准确地实现图像分类.     

基于人工蚁群优化算法的遥感图像自动分类

将人工蚁群优化算法(AACO)尝试性地引入遥感图像分类,并进行了探索性研究。作为计算智能新的分支,人工蚁群优化算法具有很强的自组织性和自适应性。因此,自然成为科学工程领域一种强有力的信息处理和解决问题的手段;AACO算法利用蚂蚁的生物特性来实现遥感图像分类等非线性操作,具有并行性、鲁棒性。初步试验分析,此方法用于遥感图像分类是有效的,在一定程度上克服传统统计分类方法与ANN方法的某些不足。本文也推动人类利用群智能在遥感图像处理及相关领域的深入研究。     

高精度合成孔径雷达图像分类算法仿真

研究合成孔径雷达图像准确性问题。合成孔径雷达图像分类过程中,特征集包括图像的Pauli特征、相干矩阵特征、小波特征、纹理特征等多特征,由于原始特征数目过多,并且采集特征伴随巨大的随机性,几乎不能建立多目标描述模式。传统的图像分类方法面临多特征、强随机性的特征集合时,因为无固定化的特征约束,导致分类效果不好的问题。为了避免上述缺陷,提出了一种基于最优分类平面的合成孔径雷达图像分类算法。利用局部二值模式纹理分析方法,进行合成孔径雷达图像特征提取,为图像分类提供准确的数据基础。利用最优分类平面方法,实现合成孔径雷达图像的分类。实验结果表明,利用上述算法进行高精度合成孔径雷达图像分类,能够获取准确的分类结果。     

基于局部特征的图像快速分类算法

基于内容的图像快速分类是Web图像实时搜索和过滤的基础。通过分析图像特征分布特点,提出一个基于局部特征的图像快速分类算法。与目前算法相比,该算法仅需对图像的局部区域扫描分析,即可得到其颜色、纹理、形状等特征,并利用Bayesian分类器来实现图像的快速自动分类。相关对比实验证实,该算法能够快速、准确地实现图像分类。     

基于SIFT算法的体育类图像分类与应用研究

针对基于内容的图像分类检索方法的数据量巨大、计算复杂度高等的不足,提出一种基于SIFT算法的图像分类方法,并将其应用到体育类图像分类上。该方法从图像中提取出特征点之后,分别使用DBScan算法和K-Mean算法对特征数据进行分析,从而得到最能反映图像特征的数据,再利用这些数据对图像进行分类。实验分析表明:该方法具有速度快、分类精度高的优点。     

基于图像表示和稀疏表示的图像分类

为了更好地实现图像分类任务,论文提出了一种新的图像分类算法,该算法可以更好地保留原始图像的大尺度信息,有效地利用原始图像的全局特征,同时减小了同一物体在其不同图像中的差异性,显著地提高了图像分类准确率。该算法首先通过新的图像表示算法生成虚拟图像,然后分别对原始图像和虚拟图像使用图像分类算法获得相应的分类误差,最后通过简单高效的误差融合方案得到最终的分类误差。实验结果表明该算法有效地降低了图像分类的错误率。     

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.