Finding the Iris Using Convolutional Neural Networks

Journal of Computer and Systems Sciences International - Iris-based identification is a well-known and widely used technology. However, its use in mobile devices is limited due to the algorithmic...     

Word Sense Disambiguation Using the Classification Information Model

A Classification Information Model is a pattern classification model.The model decides the proper class of an input instance by integrating individual decisions, each of which is made with each feature in the pattern.Each individual decision is weighted according to the distributional property of the feature deriving the decision. An individual decision and its weight are represented as classification information which is extracted from the training instances.In the word sense disambiguation based on the model, the proper sense of an input instance is determined by the weighted sum of whole individual decisions derived from the features contained in the instance.     

用改进的非监督学习方法加速前馈神经网络的训练

本语文对非学习方法和前馈神经网络的结构进行了一些简单的改进,用改进后的结构和学习方法寝化前馈神经网络的权值,使前馈神经网络的训练速度和逼近精度显著提高。最后本语文通过仿真实例验证了该方法。     

Finding Global Minima of Maximum Functions by Using Exclusion Functions without Derivatives

The first part of the paper introduces a new exclusion function without derivatives and describes its fundamental characteristics. The second part uses the new notion for finding global minimum of a real function of few variables g : [a, b] Rm R, g(x) = max{g1(x),...,gn(x)}, x [a, b], where g1(x),...,gn(x) are special multivariant real functions. The structure of the Maple program and some numerical examples are also presented in this part.     

运用动态规则集机制改善IDS性能的研究

针对高速网下IDS因性能而造成的高漏报、误报的问题,提出分析强度、分析命中率以及动态规则集的概念,建立动态规则集机制的模型,该模型可以根据网络流量和事件反馈实时动态地调整规则集的规模和分布,以提高IDS系统的整体性能,并介绍了实现中的关键技术。     

基于小波变换的影像融合在动态监测中的应用

基于小波变换的遥感影像融合是一种重要的图像信息增强方法，提出了将其应用于土地利用遥感动态监测，以自动探测土地利用发生变化的区域。方法是将某时相的多光谱影像进行主成分变换，用其第一主成分与另一时相的多光谱影像进行数据融合，融合规则是对两时相影像的小波系数进行加权平均法计算。经室内资料检核和野外验证发现，得到的变化信息的噪声小图斑较少，结果精度能满足实际应用需要。     

一种采用动态游动模式的鱼群算法

在鱼群算法优化的研究中,针对人工鱼群算法(AFSA)存在的速度慢、精度差、早熟收敛等问题,提出一种新的改进人工鱼群算法,即一种采用动态游动模式的鱼群算法(DSMFSA).上述算法让每条“鱼”具有多种搜索模式,让每条“鱼”具有机动搜索食物的能力,并可根据群体信息的反馈和自身状态随时调整搜索方式.在数值实验中选择了几个比较典型的基准函数,用来测试上述算法的性能.实验结果表明:DSMFSA算法大大改善了人工鱼群算法(AFSA)存在的易陷入局部最优、优化精度不高之不足,明显具有比AFSA好得多的优化性能.说明改进算法具有跳出局部最优的能力,可用于求解高维的复杂优化问题.     

Using the LIS as a strategic tool

A major shift in emphasis is now occurring in pathology informatics, the subdiscipline within pathology that focuses on automated information management. This shift involves a much greater emphasis on both the strategic value of the pathology database and high-level applications running on the laboratory information system (LIS).     

基于Hyperlink和相关度发现Web相关文档的研究

分析了Web文档的相似度计算方法，提出了Web上查询相关信息发现的SW0HITS算法，它结合了Web超链接、网页知识表示的信息相关度以及HITS方法来搜索Web上相关知识．本文通过它们搜索网上有关医药的信息和知识，其效果和查准率比传统HITS和IR方法有一定提高。     

对《知网》的补充以及类词典的建立

文章基于词的上下文语义环境对词进行聚类,以对语义词典《知网》进行补充,并最终得到一个基于上下文相关词的类词典。本文提出的聚类算法是在基于共现的聚类算法的基础上,对相关     

Video Behaviour Mining Using a Dynamic Topic Model

This paper addresses the problem of fully automated mining of public space video data, a highly desirable capability under contemporary commercial and security considerations. This task is especially challenging due to the complexity of the object behaviors to be profiled, the difficulty of analysis under the visual occlusions and ambiguities common in public space video, and the computational challenge of doing so in real-time. We address these issues by introducing a new dynamic topic model, termed a Markov Clustering Topic Model (MCTM). The MCTM builds on existing dynamic Bayesian network models and Bayesian topic models, and overcomes their drawbacks on sensitivity, robustness and efficiency. Specifically, our model profiles complex dynamic scenes by robustly clustering visual events into activities and these activities into global behaviours with temporal dynamics. A Gibbs sampler is derived for offline learning with unlabeled training data and a new approximation to online Bayesian inference is formulated to enable dynamic scene understanding and behaviour mining in new video data online in real-time. The strength of this model is demonstrated by unsupervised learning of dynamic scene models for four complex and crowded public scenes, and successful mining of behaviors and detection of salient events in each.     

Modeling Dynamic Hair as a Continuum

In this paper we address the difficult problem of hair dynamics, particularly hair-hair and hair-air interactions. To model these interactions, we propose to consider hair volume as a continuum. Subsequently, we treat the interaction dynamics to be fluid dynamics. This proves to be a strong as well as viable approach for an otherwise very complex phenomenon. However, we retain the individual character of hair, which is vital to visually realistic rendering of hair animation. For that, we develop an elaborate model for stiffness and inertial dynamics of individual hair strand. Being a reduced coordinate formulation, the stiffness dynamics is numerically stable and fast. We then unify the continuum interaction dynamics and the individual hair's stiffness dynamics.     

基于改进动态规划算法的复杂网络图最短路径求解

通过对复杂网络图的简化,大大缩小了计算量,对动态规划进行改进,提出广义层的概念,并利用改进的动态规划算法求得经过简化的网络图的最短路径.     

Modeling Music as a Dynamic Texture

We consider representing a short temporal fragment of musical audio as a dynamic texture, a model of both the timbral and rhythmical qualities of sound, two of the important aspects required for automatic music analysis. The dynamic texture model treats a sequence of audio feature vectors as a sample from a linear dynamical system. We apply this new representation to the task of automatic song segmentation. In particular, we cluster audio fragments, extracted from a song, as samples from a dynamic texture mixture (DTM) model. We show that the DTM model can both accurately cluster coherent segments in music and detect transition boundaries. Moreover, the generative character of the proposed model of music makes it amenable for a wide range of applications besides segmentation. As examples, we use DTM models of songs to suggest possible improvements in other music information retrieval applications such as music annotation and similarity.