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Seleção de SNPs em culturas de arroz utilizando aprendizado de máquina
(Universidade Federal de São Carlos, 2024-02-02)
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, 2023-10-06)
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, 2023-06-08)
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, 2023-04-05)
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 ...
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 ...
Aprendizado de máquina construtivo e classificação hierárquica multirrótulo aplicados à geração de moléculas
(Universidade Federal de São Carlos, 2023-02-09)
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 ...
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 ...
Estimador seletivo do conteúdo harmônico de tensão e corrente baseado em rede neural profunda
(Universidade Federal de São Carlos, 2022-04-27)
A common issue when non-linear loads are present in electric power distribution systems is voltage and/or current harmonic distortion. This power quality (PQ) problem can be mitigated, but first the harmonic components ...
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 ...