Journal ArticleDOI
A multiple frequency bands parallel spatial-temporal 3D deep residual learning framework for EEG-based emotion recognition
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TLDR
In this paper , a novel multiple frequency bands parallel spatial-temporal 3D deep residual learning framework (MFBPST-3D-DRLF) is proposed for EEG-based emotion recognition.About:
This article is published in Biomedical Signal Processing and Control.The article was published on 2023-01-01. It has received 4 citations till now. The article focuses on the topics: Computer science & Interpretability.read more
Citations
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Journal ArticleDOI
SEER-net: Simple EEG-based Recognition network
Dongyang Kuang,Craig Michoski +1 more
TL;DR: In this article , a Simple ElectroEncephalographic-based Recognition Network (SEER-net) is proposed to utilize normalized EEG signals directly as input for the purpose of end-to-end classification tasks, which achieves 90.73% mean test accuracy with 3485 parameters in the subject-dependent emotion classification tasks on SEED dataset.
Journal ArticleDOI
From gram to attention matrices: a monotonicity constrained method for eeg-based emotion classification
Journal ArticleDOI
Deep Learning Models for Stress Analysis in University Students: A Sudoku-Based Study
TL;DR: In this paper , a series of experiments were conducted to evaluate students' stress levels by engaging them in playing Sudoku games under different distracting conditions, including noisy or discordant audio, which achieved an impressive accuracy rate of 95.13% and an F1-score of 93.72%.
Journal ArticleDOI
MTLFuseNet: A novel emotion recognition model based on deep latent feature fusion of EEG signals and multi-task learning
TL;DR: Zhang et al. as mentioned in this paper proposed a novel emotion recognition model based on deep latent feature fusion of EEG signals and multi-task learning, referred to as MTLFuseNet.
References
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Proceedings Article
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe,Christian Szegedy +1 more
TL;DR: Applied to a state-of-the-art image classification model, Batch Normalization achieves the same accuracy with 14 times fewer training steps, and beats the original model by a significant margin.
Journal ArticleDOI
The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability.
Joseph L. Fleiss,Jacob Cohen +1 more
TL;DR: The use of kappa implicitly assumes that all disagreements are equally serious as discussed by the authors, which is not the case, and hence the use of the kappa scale implicitly implies that not all disagreements will be equally serious.
Journal ArticleDOI
Deep learning with convolutional neural networks for EEG decoding and visualization.
Robin Tibor Schirrmeister,Jost Tobias Springenberg,Lukas D. J. Fiederer,Martin Glasstetter,Katharina Eggensperger,Michael Tangermann,Frank Hutter,Wolfram Burgard,Tonio Ball +8 more
TL;DR: This study shows how to design and train convolutional neural networks to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping.
Journal ArticleDOI
Recognizing emotion from facial expressions: psychological and neurological mechanisms.
TL;DR: Investigations are being extended to nonhuman primates, to infants, and to patients with psychiatric disorders, to elucidate some of the mechanisms behind recognition of emotion from facial expressions.
Journal ArticleDOI
A Sparse-Group Lasso
TL;DR: A regularized model for linear regression with ℓ1 andℓ2 penalties is introduced and it is shown that it has the desired effect of group-wise and within group sparsity.