Emotion recognition in EEG signals using deep learning methods: A review
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …
planning, reasoning, and other mental states. As a result, they are considered a significant …
Exemplar Darknet19 feature generation technique for automated kidney stone detection with coronal CT images
Kidney stone is a commonly seen ailment and is usually detected by urologists using
computed tomography (CT) images. It is difficult and time-consuming to detect small stones …
computed tomography (CT) images. It is difficult and time-consuming to detect small stones …
EEG emotion recognition based on TQWT-features and hybrid convolutional recurrent neural network
M Zhong, Q Yang, Y Liu, B Zhen, B Xie - Biomedical signal processing …, 2023 - Elsevier
Electroencephalogram (EEG)-based emotion recognition has gained high attention in Brain-
Computer Interfaces. However, due to the non-linearity and non-stationarity of EEG signals …
Computer Interfaces. However, due to the non-linearity and non-stationarity of EEG signals …
QLBP: Dynamic patterns-based feature extraction functions for automatic detection of mental health and cognitive conditions using EEG signals
Background Severe psychiatric disorders, including depressive disorders, schizophrenia
spectrum disorders, and intellectual disability, have devastating impacts on vital life domains …
spectrum disorders, and intellectual disability, have devastating impacts on vital life domains …
Temporal relative transformer encoding cooperating with channel attention for EEG emotion analysis
Electroencephalogram (EEG)-based emotion computing has become a hot topic of brain-
computer fusion. EEG signals have inherent temporal and spatial characteristics. However …
computer fusion. EEG signals have inherent temporal and spatial characteristics. However …
Differential privacy scheme using Laplace mechanism and statistical method computation in deep neural network for privacy preservation
GS Kumar, K Premalatha, GU Maheshwari… - … Applications of Artificial …, 2024 - Elsevier
Mountainous amounts of information are now available in hospitals, finance, counter-
terrorism, education and many other sectors. Those information can offer a rich source for …
terrorism, education and many other sectors. Those information can offer a rich source for …
Grop: Graph orthogonal purification network for eeg emotion recognition
M Wu, CLP Chen, B Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The existence of emotion-irrelevant representations and individual variability impedes the
extraction of robust emotional representations, limiting the adaptability of EEG emotion …
extraction of robust emotional representations, limiting the adaptability of EEG emotion …
Bi-hemisphere asymmetric attention network: recognizing emotion from EEG signals based on the transformer
EEG-based emotion recognition is not only an important branch in the field of affective
computing, but is also an indispensable task for harmonious human–computer interaction …
computing, but is also an indispensable task for harmonious human–computer interaction …
Fractal spiking neural network scheme for EEG-based emotion recognition
W Li, C Fang, Z Zhu, C Chen… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Electroencephalogram (EEG)-based emotion recognition is of great significance for aiding in
clinical diagnosis, treatment, nursing and rehabilitation. Current research on this issue …
clinical diagnosis, treatment, nursing and rehabilitation. Current research on this issue …
Automated EEG sentence classification using novel dynamic-sized binary pattern and multilevel discrete wavelet transform techniques with TSEEG database
Electroencephalography (EEG) signal is an important physiological signal commonly used
in machine learning to decode brain activities, including imagined words and sentences. We …
in machine learning to decode brain activities, including imagined words and sentences. We …