Combining Classifiers
Mostrando 1-6 de 6 artigos, teses e dissertações.
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1. Combinação de modelos de campos aleatórios markovianos para classificação contextual de imagens multiespectrais / Combining markov random field models for multispectral image contextual classification
This work presents a novel MAP-MRF approach for multispectral image contextual classification by combining higher-order Markov Random Field models. The statistical modeling follows the Bayesian paradigm, with the definition of a multispectral Gaussian Markov Random Field model for the observations and a Potts MRF model to represent the a priori knowledge. In
Publicado em: 2010
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2. Differential gene expression profiles of hepatocellular carcinomas associated or not with viral infection
Chronic hepatitis B (HBV) and C (HCV) virus infections are the most important factors associated with hepatocellular carcinoma (HCC), but tumor prognosis remains poor due to the lack of diagnostic biomarkers. In order to identify novel diagnostic markers and therapeutic targets, the gene expression profile associated with viral and non-viral HCC was assessed
Brazilian Journal of Medical and Biological Research. Publicado em: 06/11/2009
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3. Combinação de múltiplos classificadores para reconhecimento de face humana
Lately, the human face object has been exploited by the advent of systems involving biometrics, especially for applications in security. One of the most challenging applications is the problem of human face recognition, which consists of determining the correspondence between an input face and an individual from a database of known persons. The process of fa
Publicado em: 2009
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4. Bootstrap agregating : an investigation of performance in statistics and neural networks classifiers, numerical evaluation and application on breast cancer diagnostic support. / Agregação via bootstrap: uma investigação de desempenho em classificadores estatísticos e redes neurais, avaliação numérica e aplicação no suporte ao diagnóstico de câncer de mama .
In pattern recognition, the medical diagnosis has received great attention. In gene-ral, the emphasis has been to identify one best model for diagnostic forecast, measured according to generalization ability. In this context, ensembles methods have been eficients, can be considered on the improvement of performance in diagnostic tasks that demand greater pre
Publicado em: 2007
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5. Combinig classifiers using knowledge rule measures and genetic algortgms / Combinação de classificadores simbólicos utilizando medidas de regras de conhecimento e algoritmos genéticos
A qualidade das hipóteses induzidas pelos atuais sistemas de aprendizado de máquina supervisionado depende da quantidade dos exemplos no conjunto de treinamento. Por outro lado, muitos dos sistemas de aprendizado de máquina conhecidos não estão preparados para trabalhar com uma grande quantidade de exemplos. Grandes conjuntos de dados são típicos em m
Publicado em: 2006
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6. Sobre publicidade direcionada baseada em conteúdo
The current boom of online advertising is associated with the revenues originated from search advertising, which has become the driving force sustaining monetization of Web services. According to Forrester Research, search advertising revenues were projected to grow from US $3.6 billion in 2004 to US $11.6 billion by 2010. Actually, numbers might be quite la
Publicado em: 2006