Now showing items 1-5 of 5
Improving land cover classification through contextual-based optimum-path forest
(Information Sciences, 2015-12-10) [Artigo]
Traditional machine learning algorithms very often assume statistically independent data samples. However, this is clearly not the case in remote sensing image applications, in which pixels present spatial and/or temporal ...
EEG-based person identification through Binary Flower Pollination Algorithm
(Expert Systems With Applications, 2016-11-15) [Artigo]
Electroencephalogram (EEG) signal presents a great potential for highly secure biometric systems due to its characteristics of universality, uniqueness, and natural robustness to spoofing attacks. EEG signals are measured ...
A Probabilistic Optimum-Path Forest Classifier for Non-Technical Losses Detection
(Ieee Transactions On Smart Grid, 2019-05-01) [Artigo]
Probabilistic-driven classification techniques extend the role of traditional approaches that output labels (usually integer numbers) only. Such techniques are more fruitful when dealing with problems where one is not ...
Robust automated cardiac arrhythmia detection in ECG beat signals
(Neural Computing & Applications, 2018-02-01) [Artigo]
Nowadays, millions of people are affected by heart diseases worldwide, whereas a considerable amount of them could be aided through an electrocardiogram (ECG) trace analysis, which involves the study of arrhythmia impacts ...
A nature-inspired approach to speed up optimum-path forest clustering and its application to intrusion detection in computer networks
(Information Sciences, 2015-02-10) [Artigo]
We propose a nature-inspired approach to estimate the probability density function (pdf) used for data clustering based on the optimum-path forest algorithm (OPFC). OPFC interprets a dataset as a graph, whose nodes are the ...