A maximum likelihood estimation (MLE) method is used to estimate the fractal dimension of a number of natural texture images with and without the presence of noise. An additional texture measure which can be linked to...
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A maximum likelihood estimation (MLE) method is used to estimate the fractal dimension of a number of natural texture images with and without the presence of noise. An additional texture measure which can be linked to the lacunarity measure is used to characterize natural textures since fractal dimension alone cannot totally characterize texture images. Segmentation of natural textures is successfully achieved by a k-means clustering algorithm using fractal dimension and the additional measure as representative features.< >
Broadband ISDN has made possible a variety of new multimedia services, but also created new problems for congestion control, due to the bursty nature of traffic sources. Lazar and Pacifici (1991) showed that traffic p...
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Broadband ISDN has made possible a variety of new multimedia services, but also created new problems for congestion control, due to the bursty nature of traffic sources. Lazar and Pacifici (1991) showed that traffic prediction is able to alleviate this problem. The traffic prediction model in their framework is a special case of the Box-Jenkins ARIMA model. In this paper, we propose a neural network approach for traffic prediction. A (1,5,1) backpropagation feedforward neural network is trained to capture the linear and nonlinear regularities in several time series. A comparison between the results from the neural network approach and the Box-Jenkins approach is also provided. The nonlinearity used in this paper is chaotic. We have designed a set of experiments to show that a neural network's prediction performance is only slightly affected by the intensity of the stochastic component (noise) in a time series. We have also demonstrated that a neural network's performance should be measured against the variance of the noise, in order to gain more insight into its behavior and prediction performance. Based on experimental results, we then conclude that the neural network approach is an attractive alternative to traditional regression techniques as a tool for traffic prediction.< >
The medial axis transform (MAT) is a sparse representation of shape, which, being reversible, has potential for binary image compression. The MAT also provides structural information not accessible with alternative bi...
Visual informatics is a field of interest not just among the information technology and computer science community, but also other related fields such as engineering, me- cal and health informatics and education start...
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ISBN:
(数字)9783642050367
ISBN:
(纸本)9783642050350
Visual informatics is a field of interest not just among the information technology and computer science community, but also other related fields such as engineering, me- cal and health informatics and education starting in the early 1990s. Recently, the field is gaining more attention from researchers and industry. It has become a mul- disciplinary and trans-disciplinary field related to research areas such as computer vision, visualization, information visualization, real-time image processing, medical image processing, image information retrieval, virtual reality, augmented reality, - pressive visual mathematics, 3D graphics, multimedia-fusion, visual data mining, visual ontology, as well as services and visual culture. Various efforts has been - vested in different research, but operationally, many of these systems are not pro- nent in the mass market and thus knowledge and research on these phenomena within the mentioned areas need to be shared and disseminated. It is for this reason that the Visual Informatics Research Group from Universiti - bangsaan Malaysia (UKM) decided to spearhead this initiative to bring together experts in this very diversified but important research area so that more concerted efforts can be undertaken not just within the visual informatics community in Malaysia but from other parts of the world, namely, Asia, Europe, Oceania, and USA. This first International Visual Informatics Conference (IVIC 2009) was conducted collaboratively, by the visual informatics research community from the various public and private institutions of higher learning in Malaysia, and hosted by UKM.
This book constitutes the proceedings of the joint International Conference APWeb/WAIM 2009 which was held in Suzhou, China, during April 1-4, 2009. The 42 full papers presented together with 26 short papers and the a...
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ISBN:
(数字)9783642006722
ISBN:
(纸本)9783642006715
This book constitutes the proceedings of the joint International Conference APWeb/WAIM 2009 which was held in Suzhou, China, during April 1-4, 2009. The 42 full papers presented together with 26 short papers and the abstracts of 2 keynote speeches were carefully reviewed and selected for inclusion in the book. The topics covered are query processing, topic-based techniques, Web data processing, multidimensional data analysis, stream data processing, data mining and its applications, and data management support to advanced applications.
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