Support Vector Machine
Mostrando 1-12 de 122 artigos, teses e dissertações.
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1. Identifying olive oil fraud and adulteration using machine learning algorithms
As olive oil (OO) is more expensive than other vegetable oils, it is usually adulterated by blending it with more economic edible oils such as cottonseed oil (CSO), canola oil (CO), and soybean oil (SO). This research aimed to determine the fatty acid compositions obtained as a result of blending different proportions of CSO, CO and SO with OO using a gas ch
Química Nova. Publicado em: 2022
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2. Applicability of computer vision in seed identification: deep learning, random forest, and support vector machine classification algorithms
ABSTRACT The use of computer image analysis can assist the extraction of morphological information from seeds, potentially serving as a resource for solving taxonomic problems that require extensive training by specialists whose primary method of examination is visual identification. We propose to test the ability of deep learning, SVM and random forest algo
Acta Bot. Bras.. Publicado em: 2021-03
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3. Multi-Step-Ahead Spectrum Prediction for Cognitive Radio in Fading Scenarios
Abstract This paper analyzes multi-step-ahead spectrum prediction for Cognitive Radio (CR) systems using several future states. A slot-based scenario is used, and prediction is based on the Support Vector Machine (SVM) algorithm. The aim is to determine whether multi-step-ahead spectrum prediction has gains in terms of reduced channel-switching and increased
J. Microw. Optoelectron. Electromagn. Appl.. Publicado em: 2020-12
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4. Diferenciação de esclerose múltipla recorrente-remitente e progressiva secundária: um estudo de ressonância magnética com espectroscopia baseado em aprendizado de máquina
RESUMO Introdução: A ressonância magnética é a ferramenta mais importante para o diagnóstico e acompanhamento na EM. A transição da EM recorrente-remitente (EMRR) para a EM progressiva secundária (EMPS) é clinicamente difícil e seria importante desenvolver a proposta apresentada neste estudo a fim de contribuir com o processo. Objetivo: o obje
Arq. Neuro-Psiquiatr.. Publicado em: 2020-12
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5. ALTERNATIVES TO ESTIMATE THE VOLUME OF INDIVIDUAL TREES IN FOREST FORMATIONS IN THE STATE OF MINAS GERAIS, BRAZIL
ABSTRACT The objective of this study was to compare different alternatives to estimate the stem volume of individual trees in four different forest formations in the Minas Gerais state, Brazil. The data were obtained in a forest inventory procedure performed by the Minas Gerais Technological Center Foundation. The stem volumes were computed by the Smalian ex
CERNE. Publicado em: 2020-09
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6. Geostatistics or machine learning for mapping soil attributes and agricultural practices
ABSTRACT Applying the upcoming technologies in agriculture has been a major economic, environmental and social challenge for scientists and farmers. In order to overcome such challenge, this study evaluated the advantages and limitations of using geostatistics and machine learning for soil mapping in agricultural practices and soil surveys. The study occurre
Rev. Ceres. Publicado em: 2020-08
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7. MULTILEVEL NONLINEAR MIXED-EFFECTS MODEL AND MACHINE LEARNING FOR PREDICTING THE VOLUME OF Eucalyptus SPP. TREES
ABSTRACT Volumetric equations is one of the main tools for quantifying forest stand production, and is the basis for sustainable management of forest plantations. This study aimed to assess the quality of the volumetric estimation of Eucalyptus spp. trees using a mixed-effects model, artificial neural network (ANN) and support-vector machine (SVM). The datab
CERNE. Publicado em: 2020-03
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8. Land-use influence on the soil hydrology: An approach in upper Grande River basin, Southeast Brazil
RESUMO A Bacia do Alto Grande (ARG) é responsável pela drenagem de vários rios no sudeste do Brasil, sendo uma região hidrológica de grande importância para o Sistema Elétrico Brasileiro. Portanto, estudos sobre a disponibilidade de água nesta região são indispensáveis para uma melhor tomada de decisão na gestão dos recursos hídricos. O objetiv
Ciênc. agrotec.. Publicado em: 09/12/2019
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9. A Novel Run-length based wavelet features for Screening Thyroid Nodule Malignancy
Abstract: Thyroid nodules are cell growths in the thyroid which might be for in one of two categories benign or malignant. Nodular thyroid disease is common and because of the associated risk of malignancy and hyper-function; these nodules have to be examined thoroughly. Hence diagnosing thyroid nodule malignancy in the early stage can mitigate the possibili
Braz. arch. biol. technol.. Publicado em: 25/11/2019
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10. Prediction of soil classes in a complex landscape in Southern Brazil
Resumo: O objetivo deste trabalho foi avaliar o uso da seleção de covariáveis por conhecimento especializado no desempenho de modelos de predição de classes de solos em uma paisagem complexa, para identificar o melhor modelo preditivo para o mapeamento digital de solos na região Sul do Brasil. Um total de 164 pontos foram amostrados em campo, com uso d
Pesq. agropec. bras.. Publicado em: 11/11/2019
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11. A NOVEL RAISIN SEGMENTATION ALGORITHM BASED ON DEEP LEARNING AND MORPHOLOGICAL ANALYSIS
ABSTRACT We propose a segmentation algorithm for raisin extraction. The proposed approach consists of the following aspects. Deep learning is used to predict the number of raisins in each connected region, and the shape features such as the roundness, area, X-axis value for the centroid, Y-axis value for the centroid, axis length and perimeter of each region
Eng. Agríc.. Publicado em: 04/11/2019
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12. Predico do Câncer de Mama com Aplicação de Modelos de Inteligência Computacional
RESUMO O uso de modelos para diagnóstico auxiliado por computador (CAD) tem sido proposto para auxiliar na detecção e classificação do câncer de mama. Neste trabalho, avaliou-se o desempenho dos modelos de rede neural de perceptrons de múltiplas camadas e máquina de vetores de suporte não linear para classificar nódulos de câncer de mama. Dez cara
TEMA (São Carlos). Publicado em: 16/09/2019