Browsing by Subject "Aprendizado de máquina"
Now showing items 1-20 of 74
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Classificação preditiva de fases para ligas multicomponentes CrCoFeMnNi utilizando machine learning
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 16/02/2023)When we refer to multicomponent alloys, or high entropy alloys as they are commonly called, it is inevitable to discuss the challenge of exploring new compositions that may be of scientific interest. This difficulty is ... -
Classificação de imagens de satélite com redes neurais convolucionais
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 06/04/2023)Satellite images are used in several areas, such as agribusiness, urban planning, environmental monitoring, among others. These images have a large and complex amount of data and the application of Machine Learning techniques ... -
Classifcação binária via Bayes Ingênuo: um estudo comparativo de predições
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 17/03/2023)In this undergraduate thesis, we propose a review of the Naive Bayes classifcation method applied to binary response variables, with a more in-depth formalization of the Gaussian Naive Bayes and Flexible Naive Bayes ... -
Algoritimo de detecção de retinopatia diabética baseado em aprendizado de máquina
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 06/04/2023)In this study, the application of neural network and machine learning techniques was explored in order to identify the presence of lesions related to diabetic retinopathy (DR) in fundus images. DR is a frequent complication ... -
Seleção de SNPs em culturas de arroz utilizando aprendizado de máquina
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 02/02/2024)Rice (Oryza sativa) is one of the largest collections of genetic resources among plant species of economic interest. To increase the productivity of this cultivar, several genetic variability studies have been developed. ... -
Desenvolvimento de novas metodologias de acoplamento C-C e/ou C-N: mesclando ciência de dados e catálise metálica
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Química - PPGQ, Câmpus São Carlos, 06/10/2023)The approach of statistical methods capable of accurately predicting the relationship between structure and reactivity represents a major impact on the development of reactions. Recently, machine learning tools have been ... -
Sistema de visão computacional para reconhecimento e classificação de padrões de famílias de plantas invasoras
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 08/06/2023)Computer Vision, in addition to involving pattern recognition and object classification techniques, has been characterized as an emerging field of fundamental importance in the context of intelligent computing. Its application ... -
Hybrid and semi-supervised predictive bi-clustering trees for interaction prediction
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 05/04/2023)Interaction data is obtained by observing and recording interactions between objects. The use of interaction data makes it possible to solve many complex problems. Currently, there are several ways to use this data to ... -
Análise comparativa entre técnicas de aprendizado de máquina aplicadas para a predição de preços de produtos hortifrutícolas
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 29/08/2023)Family farming is characterized as any form of land cultivation managed by a family, employing its own members as the main labor force. Most agricultural establishments in Brazil fit this definition, however, the area ... -
Investigação de métodos de seleção de atributos para problemas de classificação hierárquica multirrótulo
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 06/04/2023)Classification is the task of assigning data instances to classes. In Hierarchical Multi- label Classification, instances may belong to two or more classes (labels) simultaneously, where the classes are hierarchically ... -
Aprendizado de máquina para a conservação da biodiversidade: adequabilidade de habitat nas unidades de conservação do estado de São Paulo
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciências Ambientais - PPGCAm, Câmpus São Carlos, 27/02/2023)Habitat Suitability Models (HSMs) are statistical models that relate the location of species and environmental variables that restrict their distribution. They can be developed by Machine Learning algorithms, aiming to ... -
Auxílio ao diagnóstico automático do esôfago de Barrett utilizando aprendizado de máquina
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 28/03/2022)Esophageal adenocarcinoma is an illness that is usually hard to detect at the early stages in the presence of Barrett's esohagus. The development of automatic evaluation systems of such illness may be very useful, thus ... -
Análise comparativa de algoritmos de construção de grafos e técnicas de incorporação de palavras na análise de sentimentos
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 01/02/2024)Sentiment analysis has become a crucial tool for understanding public perception in various areas, such as marketing, politics, and social media. It allows the extraction of valuable insights from large volumes of text, ... -
Aprendizado de máquina construtivo e classificação hierárquica multirrótulo aplicados à geração de moléculas
(Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Ciência da Computação - PPGCC, Câmpus São Carlos, 09/02/2023)One of the goals of Medicinal Chemistry is to discover new molecules with drug-like characteristics, which is challenging because the search space is discrete, unstructured, and enormous. In recent years, computation has ... -
Previsões de preço de criptomoedas utilizando algoritmos de Aprendizado de Máquina
(Universidade Federal de São Carlos, UFSCar, , Câmpus Sorocaba, 10/10/2023)Cryptourrencies are decentralized digital currencies created with the intent of replacing traditional forms of payment. Their high volatility is one of the aspects that causes distrust among investors. Artificial Intelligence ... -
Alocação de carteiras de ações utilizando aprendizado de máquina e regras fuzzy
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 22/09/2022)Long-term investments through stock portfolios attract the attention of investors, who are looking for simple and effective ways to select stocks to compose a portfolio, as well as find a series of assets that will have ... -
Predição de interações entre piRNAs e elementos transponíveis por meio de predictive bi-clustering trees
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 26/04/2022)PIWI-interacting RNAs (PiRNAs) are a class of interfering RNAs whose actions range from regulating gene expression to fighting viral infections and silencing transposable elements, possessing unique characteristics such ... -
Detecção de defeitos em tecidos através de redes neurais convolucionais
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 03/05/2022)This work aims to apply transfer learning to a detector based on convolutional neural networks to identify defects and patterns through tissue images. With Industry 4.0, intelligent systems are increasingly being applied ... -
Redes neurais aplicadas a grafos: uma abordagem semi-supervisionada
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 18/04/2022)In this work, we propose an in-depth analysis of Graph Convolutional Networks, a semi-supervised machine learning method for node classification in graph-structured data. Based on the seminal work proposed by Thomas Kipf ... -
Utilização de métodos de aprendizado de máquina para estimação de escores de propensão
(Universidade Federal de São Carlos, UFSCar, , Câmpus São Carlos, 18/04/2022)Increasingly larger and more complex databases can be easily obtained and appropriate technologies for modeling massive amounts of data become increasingly necessary in order to optimize results and predictions. Machine ...