Titlebook: Computational Intelligence for Multimedia Understanding; International Worksh Emanuele Salerno,A. Enis Çetin,Ovidio Salvetti Conference pro

parallelism

阴郁

The Historical Roots of Strategic Agility,ems which have rather strong constraints in computational power and data transmission. Thus, such embedded platform cannot use advanced computer vision and pattern recognition methods, which are power consuming, on the other hand, the platform may be able to exploit a multi-node strategy that allows

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Computational Intelligence for Multimedia UnderstandingInternational Worksh

沉积物

Learning an Ontology for Visual Tasks,between showing and naming. The knowledge of expressing visual experience is often not trained. Therefore, a methodology is needed of how to acquire and express visual knowledge. This methodology should become a standard for visual tasks, independent of the technical or medical discipline. In this p

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Ontology and Algorithms Integration for Image Analysis, the features to be extracted depends on the image based task that has to be performed. This problem-dependency has caused the flourish of number and number of features in the literature, with a substantial disorganization of their introduction and definition. The idea behind the work reported in th

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analogous

A Bayesian Active Learning Framework for a Two-Class Classification Problem,ian modeling and inference paradigm to tackle the problem of kernel-based data classification. This Bayesian methodology is appropriate for both finite and infinite dimensional feature spaces. Parameters are estimated, using the kernel trick, following the evidence Bayesian approach from the margina

DIKE

Unsupervised Classification of SAR Images Using Hierarchical Agglomeration and EM,on Classification Expectation-Maximization (CEM). To get rid of two drawbacks of EM type algorithms, namely the initialization and the model order selection, we combine the CEM algorithm with the hierarchical agglomeration strategy and a model order selection criterion called Integrated Completed Li

Malfunction

Geometrical and Textural Component Separation with Adaptive Scale Selection,e enhancement and the quality criterion of the goal function. We apply Anisotropic Diffusion with a Total Variation based adaptive parameter estimation and automatic stopping condition. Our quality measure is based on an observation that the cartoon and the texture components of an image are orthogo

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