Titlebook: Intelligent Computer Graphics 2009; Dimitri Plemenos,Georgios Miaoulis Book 2009 Springer-Verlag Berlin Heidelberg 2009 3D.GPU.artificial

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书目名称Intelligent Computer Graphics 2009影响因子(影响力)




书目名称Intelligent Computer Graphics 2009影响因子(影响力)学科排名




书目名称Intelligent Computer Graphics 2009网络公开度




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书目名称Intelligent Computer Graphics 2009被引频次




书目名称Intelligent Computer Graphics 2009被引频次学科排名




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书目名称Intelligent Computer Graphics 2009年度引用学科排名




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书目名称Intelligent Computer Graphics 2009读者反馈学科排名

refraction

Affective States in Behavior Networks,s.Without emotions, humans cannot make reasonable choices, a fact that has until recently been neglected within the area of action selection. We propose a method to extend behavior networks to include affective impact. The work by Loewenstein .. will be our main motivation. In our model the paramete

防御

基因组

Classifying Volume Datasets Based on Intensities and Geometric Features,natomical region (head, spine, abdomen, etc.) and other parameters related to the data acquisition process. While parts of the information (imaging modality and acquisition sequence) may be obtained from the meta-data stored with the volume scan, there is important information which is not stored ex

配偶

sorbitol

An Intelligent System for Overlaying Texts on Background Images Based on Computational Aesthetics,mpose a set of test images overlaid with a paragraph of Chinese texts as the stimuli. The positions of the text overlay were determined by varying the balance in order to validate computational aesthetic quantification algorithms with subjective ratings. The stimuli were rated by 10 subjects in an e

含糊

GIST

贞洁

An SVM/GA Hybrid Framework for Qualitative Knowledge Aided 3D Scene Synthesis,ign process. Our motivation is to alleviate the task of synthesizing a scene conforming to the particularities of certain morphological or other intuitive demands. We address the feasibility of such a framework, through the study and integration of methods for the acquisition of qualitative knowledg

VEN

Machine Learning and Pattern Analysis Methods for Profiling in a Declarative Collaorative Frameworkion of a scene, personalization mechanisms are incorporated in the proposed architecture. In this paper, we examine different pattern analysis and machine intelligence algorithms for profiling in such framework. Two main approaches are described; the single (independent) profile estimation and the c