BCN Perceptual Computing Lab Repository

Visual features selection using Naïve Bayes Models

Baró, Xavier and Vitrià, Jordi (2007) Visual features selection using Naïve Bayes Models. Computer Vision: Process of research and development . pp. 54-59. ISSN 978-84-935251-4-9

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Abstract

This paper describes an object detection approach based on the use of Evolutive Algorithms based on Probability Models (EAPM), a new paradigm in evolutionary computation consisting on iteratively building a probability model to describe the space of promising solutions to a given problem. After the parametrization of the detection problem by means of the weighted dissociated dipoles, a new EAPM based on Naïve Bayes Models estimation is used to find good features.

Item Type:Article
Subjects:Q Science > QA Mathematics > QA76 Computer software
ID Code:35
Deposited By:n/d Generic User
Deposited On:03 Aug 2009 21:14
Last Modified:29 Nov 2010 17:52

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