IEEE

Explaining Deep Convolutional Neural Networks for Image Classification by Evolving Local Interpretable Model-Agnostic Explanations

Abstract: Deep convolutional neural networks (CNNs) have proven their effectiveness and are widely acknowledged as the dominant method for image classification. However, their lack of explainability ...
IEEE

Monte Carlo-Based Strategy for Assessing the Impact of EEG Data Uncertainty on Confidence in Convolutional Neural Network Classification

Abstract: Electroencephalography (EEG) data acquisition process in Brain-Computer Interfaces (BCIs) is inevitably affected by uncertainty which introduces variability in the data. This variability, ...