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GameEmo-CapsNet: Emotion Recognition from Single-Channel EEG Signals Using the 1D Capsule Networks

https://doi.org/10.18280/ts.380612
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/ima.22291openalex-snapshot
Cervical image classification based on image segmentation preprocessing and a CapsNet network model
inferredcites →https://doi.org/10.1007/978-981-15-5495-7openalex-snapshot
Bio-inspired Neurocomputing
inferredcites →https://doi.org/10.1016/j.apacoust.2020.107840openalex-snapshot
A new approach to recognition of human emotions using brain signals and music stimuli
inferredcites →https://doi.org/10.1016/j.asoc.2020.106954openalex-snapshot
EEG emotion recognition using fusion model of graph convolutional neural networks and LSTM
inferredcites →https://doi.org/10.1016/j.bbe.2020.04.005openalex-snapshot
Comparison of different feature extraction methods for EEG-based emotion recognition
inferredcites →https://doi.org/10.1016/j.bspc.2019.101756openalex-snapshot
EEG-based emotion recognition using simple recurrent units network and ensemble learning
inferredcites →https://doi.org/10.1016/j.bspc.2020.101867openalex-snapshot
Automated emotion recognition based on higher order statistics and deep learning algorithm
inferredcites →https://doi.org/10.1016/j.bspc.2020.101951openalex-snapshot
Database for an emotion recognition system based on EEG signals and various computer games – GAMEEMO
inferredcites →https://doi.org/10.1016/j.bspc.2020.102389openalex-snapshot
Emotion recognition from EEG signals using empirical mode decomposition and second-order difference plot
inferredcites →https://doi.org/10.1016/j.chaos.2020.110122openalex-snapshot
Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks
inferredcites →https://doi.org/10.1016/j.chaos.2021.110671openalex-snapshot
A new fractal pattern feature generation function based emotion recognition method using EEG
inferredcites →https://doi.org/10.1016/j.comcom.2020.02.051openalex-snapshot
Emotion recognition from spatiotemporal EEG representations with hybrid convolutional recurrent neural networks via wearable multi-channel headset
inferredcites →https://doi.org/10.1016/j.ejmp.2020.01.007openalex-snapshot
1D-CADCapsNet: One dimensional deep capsule networks for coronary artery disease detection using ECG signals
inferredcites →https://doi.org/10.1016/j.inffus.2018.10.009openalex-snapshot
Human emotion recognition using deep belief network architecture
inferredcites →https://doi.org/10.1016/j.irbm.2021.01.004openalex-snapshot
COVID-19 Detection System Using Chest CT Images and Multiple Kernels-Extreme Learning Machine Based on Deep Neural Network
inferredcites →https://doi.org/10.1016/j.jclepro.2020.124022openalex-snapshot
Artificial intelligence in nuclear industry: Chimera or solution?
inferredcites →https://doi.org/10.1016/j.jneumeth.2020.108904openalex-snapshot
Single-trial EEG emotion recognition using Granger Causality/Transfer Entropy analysis
inferredcites →https://doi.org/10.1016/j.knosys.2020.106243openalex-snapshot
EEG-based emotion recognition using an end-to-end regional-asymmetric convolutional neural network
inferredcites →https://doi.org/10.1016/j.measurement.2019.107003openalex-snapshot
Dynamic entropy-based pattern learning to identify emotions from EEG signals across individuals
inferredcites →https://doi.org/10.1016/j.neucom.2015.05.030openalex-snapshot
Could linear model bridge the gap between low-level statistical features and aesthetic emotions of visual textures?
inferredcites →https://doi.org/10.1016/j.neucom.2020.05.078openalex-snapshot
Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications
inferredcites →https://doi.org/10.1016/j.neucom.2020.12.098openalex-snapshot
NeuroSense: Short-term emotion recognition and understanding based on spiking neural network modelling of spatio-temporal EEG patterns
inferredcites →https://doi.org/10.1016/j.neuropsychologia.2020.107506openalex-snapshot
Emotion recognition with convolutional neural network and EEG-based EFDMs
inferredcites →https://doi.org/10.1037/0033-295x.110.1.145openalex-snapshot
Core affect and the psychological construction of emotion.
inferredcites →https://doi.org/10.1080/02699939208411068openalex-snapshot
An argument for basic emotions
inferredcites →https://doi.org/10.1109/siu.2018.8404385openalex-snapshot
Recognition of sign language using capsule networks
inferredcites →https://doi.org/10.1186/s40708-020-00111-3openalex-snapshot
Two-stepped majority voting for efficient EEG-based emotion classification
inferredcites →https://doi.org/10.18280/ts.360502openalex-snapshot
WPT-ANN and Belief Theory Based EEG/EMG Data Fusion for Movement Identification
inferredcites →https://doi.org/10.18280/ts.370617openalex-snapshot
Preictal and Interictal Recognition for Epileptic Seizure Prediction Using Pre-trained 2D-CNN Models
inferredcites →https://doi.org/10.3390/s19092212openalex-snapshot
Emotion Recognition from Multiband EEG Signals Using CapsNet

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4657124openalex-extracted
inferred← citeshttps://doi.org/10.1007/978-3-031-24801-6_18openalex-snapshot
A Pyramidal Approach for Emotion Recognition from EEG Signals
inferred← citeshttps://doi.org/10.1007/s10462-023-10690-2openalex-snapshot
Role of machine learning and deep learning techniques in EEG-based BCI emotion recognition system: a review
inferred← citeshttps://doi.org/10.1007/s11760-022-02381-2openalex-snapshot
FL-CapsNet: facial localization augmented capsule network for human emotion recognition
inferred← citeshttps://doi.org/10.1016/b978-0-323-95439-6.00008-9openalex-snapshot
Recent development of single-channel EEG-based automated sleep stage classification: Review and future perspectives
inferred← citeshttps://doi.org/10.1016/j.asoc.2024.112301openalex-snapshot
Automated EEG-based language detection using directed quantum pattern technique
inferred← citeshttps://doi.org/10.1016/j.medengphy.2025.104316openalex-snapshot
A simple algorithm for primary emotion recognition from dual channel EEG signals
inferred← citeshttps://doi.org/10.1016/j.neucom.2024.129073openalex-snapshot
Context-based emotion recognition: A survey
inferred← citeshttps://doi.org/10.1109/ciacon70148.2026.11688442openalex-snapshot
Comparative Evaluation of Nonlinear and Spectral EEG Features for Game-Evoked Cognitive Engagement
inferred← citeshttps://doi.org/10.1109/jiot.2023.3320269openalex-snapshot
A Novel Emotion Recognition Method Based on the Feature Fusion of Single-Lead EEG and ECG Signals
inferred← citeshttps://doi.org/10.1142/s0219519424400049openalex-snapshot
A CONSUMER SENTIMENT ANALYSIS METHOD BASED ON EEG SIGNALS AND A RESNEXT MODEL
inferred← citeshttps://doi.org/10.3390/app121910028openalex-snapshot
A Novel Approach for Emotion Recognition Based on EEG Signal Using Deep Learning
inferred← citeshttps://doi.org/10.3390/diagnostics13223437openalex-snapshot
Classification of Emotional and Immersive Outcomes in the Context of Virtual Reality Scene Interactions
inferred← citeshttps://doi.org/10.3390/s22145252openalex-snapshot
EEG Emotion Classification Network Based on Attention Fusion of Multi-Channel Band Features
inferred← citeshttps://doi.org/10.4018/979-8-3373-5702-7.ch011openalex-snapshot
EEGNet-Based Emotion Recognition Using Multimodal EEG and ECG Signals
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