Color indexing

Computer vision is embracing a new research focus in which the aim is to develop visual skills for robots that allow them to interact with a dynamic, realistic environment. To achieve this aim, new kinds of vision algorithms need to be developed which run in real time and subserve the robot's goals. Two fundamental goals are determining the location of a known object. Color can be successfully used for both tasks.This article demonstrates that color histograms of multicolored objects provide a robust, efficient cue for indexing into a large database of models. It shows that color histograms are stable object representations in the presence of occlusion and over change in view, and that they can differentiate among a large number of objects. For solving the identification problem, it introduces a technique calledHistogram Intersection, which matches model and image histograms and a fast incremental version of Histogram Intersection, which allows real-time indexing into a large database of stored models. For solving the location problem it introduces an algorithm calledHistogram Backprojection, which performs this task efficiently in crowded scenes.  

Agent研究现状与发展趋势

对有关Agent理论和实践两方面的研究现状、关键技术和发展趋势进行了综述和讨论，试图勾画出目前Agent研究的脉络、重点及其发展趋向.主要内容包括：（1）智能Agent的特性、表示和推理；（2）多Agent系统的联合意图、协商和规划；（3）面向Agent的程序设计.最后，简单讨论了Agent技术目前所面临的挑战.  

关联规则的增量式更新算法

关联规则的开采是一个重要的数据开采问题.目前已经提出了许多算法用于高效地发现大规模数据库中的关联规则，而对关联规则维护问题的研究工作却很少.在用户开采关联规则的交互过程中，为了找到真正令其感兴趣的规则，用户将需要不断调整两个描述用户兴趣程度的阈值：最小支持度和最小可信度.本文提出了两种增量式更新算法——IUA(incremental updating algorithm)和PIUA(parallel incremental updating algorithm),用来解决这一关联规则高效维护问题.  

云计算:系统实例与研究现状

针对云计算这样一个范畴综述了当前云计算所采用的技术,剖析其背后的技术含义以及当前云计算参与企业所采用的云计算实现方案.云计算包含两个方面的含义:一方面是底层构建的云计算平台基础设施,是用来构造上层应用程序的基础;另外一方面是构建在这个基础平台之上的云计算应用程序.主要是针对云计算的基础架构的研究与实现状况给出综述,对于云计算的应用也有所涉及.云计算有3个最基本的特征:第1个是基础设施架构在大规模的廉价服务器集群之上;第二是应用程序与底层服务协作开发,最大限度地利用资源;第3个是通过多个廉价服务器之间的冗余,通过软件获得高可用性.云计算达到了两个分布式计算的重要目标:可扩展性和高可用性.可扩展性表达了云计算能够无缝地扩展到大规模的集群之上,甚至包含数千个节点同时处理.高可用性代表了云计算能够容忍节点的错误,甚至有很大一部分节点发生失效也不会影响程序的正确运行.通过此文可以了解云计算的当前发展状况以及未来的研究趋势.  

Performance of optical flow techniques

While different optical flow techniques continue to appear, there has been a lack of quantitative evaluation of existing methods. For a common set of real and synthetic image sequences, we report the results of a number of regularly cited optical flow techniques, including instances of differential, matching, energy-based, and phase-based methods. Our comparisons are primarily empirical, and concentrate on the accuracy, reliability, and density of the velocity measurements; they show that performance can differ significantly among the techniques we implemented.  

植物生长建模与可视化——回顾与展望

回顾了植物生长的建模与可视化研究.为了加深对不同模型的目的、内涵与局限性的 理解,该文对植物生长模型进行了分类.在植物生长机研究中,对目前常见的分形方法、随机过 程、人工智能等建模方法的特点进行了比较分析.分别介绍了植物仿真与可视化方面的研究进 展及其相关技术,以及植物生长软件的发展状况.最后,总结了该领域研究中存在的主要问题, 并讨论了未来研究与应用方面的发展趋向及其前景.  

Unsupervised texture segmentation using Gabor filters

This paper presents a texture segmentation algorithm inspired by the multi-channel filtering theory for visual information processing in the early stages of human visual system. The channels are characterized by a bank of Gabor filters that nearly uniformly covers the spatial-frequency domain, and a systematic filter selection scheme is proposed, which is based on reconstruction of the input image from the filtered images. Texture features are obtained by subjecting each (selected) filtered image to a nonlinear transformation and computing a measure of “energy” in a window around each pixel. A square-error clustering algorithm is then used to integrate the feature images and produce a segmentation. A simple procedure to incorporate spatial information in the clustering process is proposed. A relative index is used to estimate the “true” number of texture categories.  

Architecture for an artificial immune system

An artificial immune system (ARTIS) is described which incorporates many properties of natural immune systems, including diversity, distributed computation, error tolerance, dynamic learning and adaptation, and self-monitoring. ARTIS is a general framework for a distributed adaptive system and could, in principle, be applied to many domains. In this paper, ARTIS is applied to computer security in the form of a network intrusion detection system called LISYS. LISYS is described and shown to be effective at detecting intrusions, while maintaining low false positive rates. Finally, similarities and differences between ARTIS and Holland's classifier systems are discussed.  

云计算及其关键技术

云计算是一种新兴的计算模型,它是在网格计算的基础上发展而来的.介绍了云计算的发展历史和应用场景,比较了现有的云计算的定义并给出了新的定义,以谷歌的云计算技术为例,总结了云计算的关键技术:数据存储技术(Google File System)、数据管理技术(BigTable)、编程模型和任务调度模型(Map-Reduce)等,分析了云计算和网格计算以及传统超级计算的区别,并指出了云计算的广阔发展前景.  

基于粗糙集的多变量决策树构造方法

本文利用粗糙集理论中条件属性相对于决策属性的核，解决多变量检验中属性的选择问题．另外，定义了２个等价关系相对泛化的概念，并将它用于解决多变量检验的构造问题．通过一个例子，对本文提出的多变量决策树方法与著名的单变量决策树（ＩＤ３）方法进行了比较，结果表明前者比后者更简单．同时，对几种多变量决策树方法做了初步的对比分析．