Oct 1, 2023 · In this study, we investigated the effectiveness of multi-task learning (MTL) for raw EEG-based convolutional neural networks (CNNs) in emotion recognition ...
Oct 1, 2023 · In this study, we investigated the effectiveness of multi-task learning (MTL) for raw EEG-based convolutional neural networks (CNNs) in emotion recognition ...
Effectiveness of Multi-Task Deep Learning Framework for Eeg-Based ...
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Jan 29, 2023 · This shows that the MTL can be a promising method for emotion recognition in utilizing the raw EEG-based CNN classifiers and emphasizes the ...
Our results showed that (1) the MTL classifier had a significantly higher classification accuracy and improved the performance of the single-task learnings ( ...
28 investigated the effectiveness of multi-task learning for emotion recognition using raw EEGbased convolutional neural networks (CNNs) with auxiliary context ...
This paper examines contemporary research that challenges traditional assumptions about the role of emotions in consumer decision-making and introduces the role ...
May 23, 2024 · The article analyzes trends in human emotion recognition via EEG signals, with a focus on datasets, classifiers, and research contributions.
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In this study, we introduce an innovative EEG signal reconstruction sub-module designed to enhance the performance of deep learning models on EEG eye-tracking ...
Deep learning (DL) technologies have recently shown great potential in emotion recognition based on electroencephalography (EEG). However, existing DL-based ...
This paper aims to provide an up-to-date and comprehensive survey of EEG emotion recognition, especially for various deep learning techniques in this area.