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Auxílio ao diagnóstico automático do esôfago de Barrett utilizando aprendizado de máquina
(Universidade Federal de São Carlos, 2022-03-28)
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 ...
Conditional independence testing, two sample comparison and density estimation using neural networks
(Universidade Federal de São Carlos, 2020-08-03)
Given the vast amount of data available nowadays and the rapid increase of computational processing power, the field of machine learning and the so called algorithmic modeling have seen a recent surge in its popularity and ...
Análise da predição da violência infantil por meio de árvores de decisão e regras de associação
(Universidade Federal de São Carlos, 2020-06-02)
According to the United Nations International Children's Emergency Fund (UNICEF), currently around 300 million children around the world suffer from various types of abuse, including: psychological, physical, sexual or ...
OxiTidy: motion artifact detection-reduction in photoplethysmographic signals using artificial neural networks
(Universidade Federal de São Carlos, 2022-07-22)
Nowadays, technological evolution has allowed advances in several areas, especially in healthcare. Digital transformation in health has brought benefits to both professionals and patients. What was possible to do only with ...
Método para classificação de padrões da Lagarta do cartucho (Spodoptera frugiperda) na cultura do milho baseado em processamento de imagens digitais e aprendizado de máquina
(Universidade Federal de São Carlos, 2021-12-29)
The detection, identification, and control of the Fall Armyworm (Spodoptera frugperda) pest
into the maize culture (Zea mays) are greatly dependent on the human factor. Currently, such
control occurs mainly through the ...
Scalable and interpretable kernel methods based on random Fourier features
(Universidade Federal de São Carlos, 2023-03-29)
Kernel methods are a class of statistical machine learning models based on positive semidefinite kernels, which serve as a measure of similarity between data features. Examples of kernel methods include kernel ridge ...
Bandas de predição usando densidade condicional estimada e um modelo LDA com covariáveis
(Universidade Federal de São Carlos, 2021-10-15)
Machine learning methods are divided into two main groups: supervised and unsupervised
methods. In the first part of this work, we develop a method for creating prediction bands
that can be applied to supervised problems. ...
Uma abordagem baseada em árvores de decisão para a análise da estabilidade angular do rotor
(Universidade Federal de São Carlos, 2021-12-06)
The power system security assessment is essential to ensure the supply of electrical
energy and the feasibility of the operation. Among these analyses, the study of the rotor
angle stability aims to ensure that the ...
Data preparation pipeline recommendation via meta-learning
(Universidade Federal de São Carlos, 2021-05-26)
Data preparation is a essential stage in the machine learning pipeline, aiming to convert noisy and disordered data into refined data compatible with the algorithms. However, data preparation is time-consuming and requires ...
Curriculum learning applied to the combined algorithm selection and hyperparameter optimization problem
(Universidade Federal de São Carlos, 2021-05-25)
AutoML has the goal to find the best Machine Learning (ML) pipeline in a complex and high dimensional search space by evaluating multiple algorithm configurations. Training multiple ML algorithms is time costly, and as ...