Combination Of Classifiers
Mostrando 1-12 de 15 artigos, teses e dissertações.
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1. Algoritmo de aprendizado supervisionado - baseado em máquinas de vetores de suporte - uma contribuição para o reconhecimento de dados desbalanceados / Supervised learning Algorithm - Based on Support Vector Machines - A Contribution to the Recognition of Unbalanced Data
The machine learning in datasets that have unbalanced classes, has received considerable attention in the scientific community, because the traditional classification algorithms dont provide a satisfactory performance. This low performance can be explained by the fact that the traditional techniques of machine learning consider that each class present in the
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 26/09/2011
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2. Aplicação de modelos de Markov ocultos na obtenção de taxas de mortalidade das larvas do mosquito da Dengue
In order to prevent the proliferation of Dengue transmitter - scientifically named as Aedes ae- gypti - and therefore decrease human contamination by such insect, many larvaecides have been developed recently. Researchers from Dom Bosco Catholic University evaluate the efectiveness of vegetal-derived substances capable to combat such animal larvae. Death rat
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 26/02/2010
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3. 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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4. Semi-supervised learning based in disagreement by similarity / Classificação semi-supervisionada baseada em desacordo por similaridade
Semi-supervised learning is a machine learning paradigm in which the induced hypothesis is improved by taking advantage of unlabeled data. Semi-supervised learning is particularly useful when labeled data is scarce and difficult to obtain. In this context, the Cotraining algorithm was proposed. Cotraining is a widely used semisupervised approach that assumes
Publicado em: 2010
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5. APLICAÇÃO DE TÉCNICAS DE APRENDIZADO DE MÁQUINA PARA CLASSIFICAÇÃO DE DEPÓSITOS MINERAIS BASEADA EM MODELO TEOR-TONELAGEM / APPLICATION OF MACHINE LEARNING TECHNIQUES FOR CLASSIFICATION OF MINERAL DEPOSITS CONTENT-BASED MODEL TONNAGE
Classification of mineral deposits into types is traditionally done by experts. Since there are reasons to believe that computational techniques can aid this classification process and make it less subjective, the research and investigation of different methods of clustering and classification to this domain may be appropriate. The way followed by researches
Publicado em: 2010
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6. 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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7. A machine learning approach to automatic music genre classification
This paper presents a non-conventional approach for the automatic music genre classification problem. The proposed approach uses multiple feature vectors and a pattern recognition ensemble approach, according to space and time decomposition schemes. Despite being music genre classification a multi-class problem, we accomplish the task using a set of binary c
Journal of the Brazilian Computer Society. Publicado em: 2008-09
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8. Dilema da diversidade-acurácia: um estudo empírico no contexto de multiclassificadores
Multi-classifier systems, also known as ensembles, have been widely used to solve several problems, because they, often, present better performance than the individual classifiers that form these systems. But, in order to do so, its necessary that the base classifiers to be as accurate as diverse among themselves this is also known as diversity/accuracy dile
Publicado em: 2008
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9. Análise de estruturas de rede neocognitron para aplicação no reconhecimento facial
The present work consists in the use of the combination of neocognitron networks for the face recognition tasks integrating a system of face recognition, categorized as holistic method, by the fact of to approach all the face in the extration of the characteristics of the input image. The use of the face as biometric attribute in the recognition of individuo
Publicado em: 2008
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10. Caracterização do teor de nitrogênio foliar e produtividade do feijoeiro com técnicas de visão artificial / Characterization of leaf nitrogen content of bean plants with techniques of machine vision
Beans are one of the basic human nutrition components in Brazil and an important source of protein. Brazil is the major world producer and consumer, but has an average yield less than that of the USA and China. In the last years, the necessity to efficiently increase crop productivity and keep concerning with environmental issues has increased the producer i
Publicado em: 2008
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11. Geração, seleção e combinação de componentes para ensembles de redes neurais aplicadas a problemas de classificação / Generation, selection and combination of components in neural network ensembles applied to classification problems
O uso da abordagem ensembles tem sido bastante explorado na última década, por se tratar de uma técnica simples e capaz de aumentar a capacidade de generalização de soluções baseadas em aprendizado de máquina. No entanto, para que um ensemble seja capaz de promover melhorias de desempenho, os seus componentes devem apresentar bons desempenhos individ
Publicado em: 2006
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12. 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