Statistical Classifiers
Mostrando 1-12 de 20 artigos, teses e dissertações.
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1. Multinomial Logistic Regression and Random Forest Classifiers in Digital Mapping of Soil Classes in Western Haiti
ABSTRACT Digital soil mapping (DSM) has been increasingly used to provide quick and accurate spatial information to support decision-makers in agricultural and environmental planning programs. In this study, we used a DSM approach to map soils in western Haiti and compare the performance of the Multinomial Logistic Regression (MLR) with Random Forest (RF) to
Rev. Bras. Ciênc. Solo. Publicado em: 02/07/2018
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2. Técnicas de visão computacional aplicadas ao reconhecimento de cenas naturais e locomoção autônoma em robôs agrícolas móveis / Computer vision techniques applied to natural scenes recognition and autonomous locomotion of agricultural mobile robots
O emprego de sistemas computacionais na Agricultura de Precisão (AP) fomenta a automação de processos e tarefas aplicadas nesta área, precisamente voltadas à inspeção e análise de culturas agrícolas, e locomoção guiada/autônoma de robôs móveis. Neste contexto, no presente trabalho foi proposta a aplicação de técnicas de visão computacional
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 09/08/2011
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3. Análise de imagem polarimétrica TerraSAR-X para classificação de uso e cobertura da terra na porção sudoeste da Amazônia Brasileira / TerraSAR-X image for classification the land use and land cover in the southwest portion of the Brazilian Amazon
The objective of this study is to analyze the potential use of images from satellite TerraSAR-X, at StripMap acquisition mode, to map and identify the land use and land cover (LULC) in the southwestern Brazilian Amazon. Classifiers based on statistical functions for maximum likelihood (ML) method and based on frequency-based contextual and neural network cla
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 24/02/2011
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4. Reconhecimento de padrões em imagens por descritores de forma / Pattern recognition in images via shape descriptors
A idéia de capacitar uma máquina a reconhecer o ambiente em que atua tem motivado pesquisadores a investir esforços no estudo do mais complexo dos sentidos humanos, a visão. A visão é, antes de tudo, uma tarefa de representação e processamento de informações, sendo portanto adequada ao tratamento computacional. Visto que ainda não se possuem méto
Publicado em: 2011
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5. Identificação de bovinos através de reconhecimento de padrões do espelho nasal utilizando redes neurais artificiais / Identification of bovines through recognition of images patterns of the muzzle using artificial neural nets
Artificial Neural Networks (ANN) are mathematical models associated with artificial intelligence that can learn and generalize information, therefore they can be used as images classifiers. This paper aims to analyze the cattle muzzle in order to prove that it is a unique and permanent characteristic of the animal thus, being used as its unique identificatio
Publicado em: 2011
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6. 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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7. 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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8. Geração genética de classificador fuzzy intervalar do tipo-2
The objective of this work is to study, expand and evaluate the use of interval type-2 fuzzy sets in the knowledge representation for fuzzy inference systems, specifically for fuzzy classifiers, as well as its automatic generation form data sets, by means of genetic algorithms. This work investigates the use of such sets focussing the issue of balance betwee
Publicado em: 2009
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9. Metodologia de estimação de idade óssea baseada em características métricas utilizando mineradores de dados e classificador neural / Methodology for bone age estimation based on metric characteristics using data mining and neural classifier
Este trabalho apresenta uma proposta de metodologia de estimação de idade óssea baseada em características métricas, utilizando o banco de imagens carpais da Escola de Engenharia de São Carlos (EESC). As imagens foram devidamente segmentadas para obtenção da área, perímetro e comprimento de cada osso, gerando, assim, um banco de dados métricos o C
Publicado em: 2009
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10. Avaliação de métodos não-supervisionados de seleção de atributos para mineração de textos / Evaluation of unsupervised feature selection methods for Text Mining
Feature selection is an activity sometimes necessary to obtain good results in machine learning tasks. In Text Mining, reducing the number of features in a text base is essential for the effectiveness of the process and the comprehensibility of the extracted knowledge, since it deals with high dimensionalities and sparse contexts. When dealing with contexts
Publicado em: 2009
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11. 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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12. 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