Using histograms to detect and track objects in color video
M Mason, Z Duric - … (AIPR 2001). Analysis and Understanding of …, 2001 - ieeexplore.ieee.org
Two methods of detecting and tracking objects in color video are presented. Color and edge
histograms are explored as ways to model the background and foreground of a scene. The …
histograms are explored as ways to model the background and foreground of a scene. The …
Rule induction for classification using multi-objective genetic programming
AP Reynolds, B de la Iglesia - International Conference on Evolutionary …, 2007 - Springer
Multi-objective metaheuristics have previously been applied to partial classification, where
the objective is to produce simple, easy to understand rules that describe subsets of a class …
the objective is to produce simple, easy to understand rules that describe subsets of a class …
JavaSpaces–an affordable technology for the simple implementation of reusable parallel evolutionary algorithms
C Setzkorn, RC Paton - … Symposium on Knowledge Exploration in Life …, 2004 - Springer
Evolutionary algorithms are powerful optimisation methods and have been applied
successfully in many scientific areas including life sciences. However, they have high …
successfully in many scientific areas including life sciences. However, they have high …
Evolving sets of symbolic classifiers into a single symbolic classifier using genetic algorithms
FC Bernardini, RC Prati… - 2008 Eighth International …, 2008 - ieeexplore.ieee.org
For a given data set, different learning algorithms typically provide different classifiers.
Although it is possible to simply select the most successful classifier, the less successful …
Although it is possible to simply select the most successful classifier, the less successful …
[PDF][PDF] On the use of multi-objective evolutionary algorithms for classification rule induction
C Setzkorn - 2005 - academia.edu
The extraction of comprehensible and general classifiers from data in the form of rule
systems is an important task within many problem domains. This thesis proposes and …
systems is an important task within many problem domains. This thesis proposes and …
Computação Evolutiva para a Construção de Regras de Conhecimento com Propriedades Específicas
AD Pila - 2007 - teses.usp.br
A maioria dos algoritmos de aprendizado de máquina simbólico utilizam regras de
conhecimento if-then como linguagem de descrição para expressar o conhecimento …
conhecimento if-then como linguagem de descrição para expressar o conhecimento …
[PDF][PDF] MERBIS-A Self-Adaptive Multi-Objective Evolutionary Rule Base Induction System
C Setzkorn, RC Paton - 2003 - Citeseer
Supervised classification is a particular data-mining task that forms part of the knowledge
discovery process. Its objectives are to extract accurate, comprehensible and interesting …
discovery process. Its objectives are to extract accurate, comprehensible and interesting …
Classification and Survival Analysis Using Multi-objective Evolutionary Algorithms
C Setzkorn - Multi-Objective Evolutionary Algorithms for Knowledge …, 2008 - Springer
Model extraction from data has at least three objectives. It aims to produce accurate,
comprehensible and interesting models. Hence, multi-objective evolutionary algorithms are …
comprehensible and interesting models. Hence, multi-objective evolutionary algorithms are …
[PDF][PDF] Combinaçao de Classificadores Simbólicos Utilizando Medidas de Avaliaçao de Regras e Algoritmos Genéticos
FC Bernardini, MC Monard - professores.uff.br
A qualidade das hipóteses induzidas pelos atuais sistemas de aprendizado de máquina
supervisionado depende da quantidade dos exemplos no conjunto de treinamento. Por …
supervisionado depende da quantidade dos exemplos no conjunto de treinamento. Por …