The Mobile Agent is thought to be the popular computing model for the next generation's distributed sys-tem. The mobile agent has the following key features: autonomy, collaboration, security and especially mobili...
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The Mobile Agent is thought to be the popular computing model for the next generation's distributed sys-tem. The mobile agent has the following key features: autonomy, collaboration, security and especially mobility. Agood communication model for mobile agents cooperation is also necessary. In this article, after describing the maincommunication mechanisms, we analyze the methods to solve Agent Tracking and Communication Failure and makeclassification. We also propose a reliable and efficient mechanism named MEFS which uses Detecting methods andthen analyze its performance by giving the experimental data at the end.
There are so many multimedia resources now. But it is difficult to look for any video thing amongthem. MPEG-4 is a major technique used for video coding. In the paper,some methods based on MPEG-4 coding stan-dard for ...
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There are so many multimedia resources now. But it is difficult to look for any video thing amongthem. MPEG-4 is a major technique used for video coding. In the paper,some methods based on MPEG-4 coding stan-dard for video retrival are introduced. The focus is on converting video data to textual data,then video retrival is con-verted to textual retrival. XML technique is involved naturally.
Interpreting background is very important in natural scene images. This paper addresses the automaticclassification of background region by using visual semantic template. The method to create the templates is intro-d...
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Interpreting background is very important in natural scene images. This paper addresses the automaticclassification of background region by using visual semantic template. The method to create the templates is intro-duced first. Then we use these templates to classify background regions, and the results are analyzed. We also usethese templates to locate background objects in images, and to determine whether an image contains certain kind ofbackground. The result is promising in object locating. Some approaches to improve the ability of these templates arealso discussed.
A novel and fast shape classification and regularization algorithm for on-line sketchy graphics recognition is proposed. We divide the on-line graphics recognition process into four stages: preprocessing,shape classif...
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A novel and fast shape classification and regularization algorithm for on-line sketchy graphics recognition is proposed. We divide the on-line graphics recognition process into four stages: preprocessing,shape classification,shape fitting,and regularization. Attraction Force Model is employed to progressively combine the vertices on the input sketchy stroke and reduce the total number of vertices before the type of shape can be determined. After that ,the shape is fitted and gradually rectified to a regular one,thus the regularized shape fits the user intended one *** results show that this algorithm can yield good recognition precision(averagely above 90% )and fine regularization effect but with fast speed. Consequently,it is especially suitable to computational critical environment such as PDAs,which solely depends on a pen-based user interface.
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