112 citations · 181 across the 5 of their papers we have counts for
5 papers
Comparison of Neural Models for X-ray Image Classification in COVID-19 Detection
Jimi Togni, Romis Attux
This study presents a comparative analysis of methods for detecting COVID-19 infection in radiographic images. The images, sourced from publicly available datasets, were categorize…
FBDNN: Filter Banks and Deep Neural Networks for Portable and Fast Brain-Computer Interfaces
Pedro R. A. S. Bassi, Romis Attux
Objective: To propose novel SSVEP classification methodologies using deep neural networks (DNNs) and improve performances in single-channel and user-independent brain-computer inte…
COVID-19 detection using chest X-rays: is lung segmentation important for generalization?
Pedro R. A. S. Bassi, Romis Attux
Purpose: we evaluated the generalization capability of deep neural networks (DNNs), trained to classify chest X-rays as Covid-19, normal or pneumonia, using a relatively small and…
Transfer Learning and SpecAugment applied to SSVEP Based BCI Classification
Pedro R. A. S. Bassi, Willian Rampazzo, Romis Attux
Objective: We used deep convolutional neural networks (DCNNs) to classify electroencephalography (EEG) signals in a steady-state visually evoked potentials (SSVEP) based single-cha…
A Deep Convolutional Neural Network for COVID-19 Detection Using Chest X-Rays
Pedro R. A. S. Bassi, Romis Attux
Purpose: We present image classifiers based on Dense Convolutional Networks and transfer learning to classify chest X-ray images according to three labels: COVID-19, pneumonia and…