[PDF][PDF] Facial expression recognition based on deep learning convolution neural network: A review
SMS Abdullah, AM Abdulazeez - Journal of Soft Computing …, 2021 - publisher.uthm.edu.my
Facial emotional processing is one of the most important activities in effective calculations,
engagement with people and computers, machine vision, video game testing, and consumer …
engagement with people and computers, machine vision, video game testing, and consumer …
Current trends and opportunities in the methodology of electrodermal activity measurement
Electrodermal activity (EDA) has been measured in the laboratory since the late 1800s.
Although the influence of sudomotor nerve activity and the sympathetic nervous system on …
Although the influence of sudomotor nerve activity and the sympathetic nervous system on …
VGGCOV19-NET: automatic detection of COVID-19 cases from X-ray images using modified VGG19 CNN architecture and YOLO algorithm
A Karacı - Neural Computing and Applications, 2022 - Springer
X-ray images are an easily accessible, fast, and inexpensive method of diagnosing COVID-
19, widely used in health centers around the world. In places where there is a shortage of …
19, widely used in health centers around the world. In places where there is a shortage of …
EEG emotion recognition based on enhanced SPD matrix and manifold dimensionality reduction
Recently, Riemannian geometry-based pattern recognition has been widely employed to
brain computer interface (BCI) researches, providing new idea for emotion recognition …
brain computer interface (BCI) researches, providing new idea for emotion recognition …
A deep learning process anomaly detection approach with representative latent features for low discriminative and insufficient abnormal data
Y Gao, X Yin, Z He, X Wang - Computers & Industrial Engineering, 2023 - Elsevier
Anomaly detection in industrial processes is vital for yield improvement and cost reduction.
With the development of sensor system and information technology, industrial big data …
With the development of sensor system and information technology, industrial big data …
Automated affective computing based on bio-signals analysis and deep learning approach
Extensive possibilities of applications have rendered emotion recognition ineluctable and
challenging in the fields of computer science as well as in human-machine interaction and …
challenging in the fields of computer science as well as in human-machine interaction and …
1D convolutional autoencoder-based PPG and GSR signals for real-time emotion classification
DH Kang, DH Kim - IEEE Access, 2022 - ieeexplore.ieee.org
To apply emotion recognition and classification technology to the field of human-robot
interaction, it is necessary to implement fast data processing and model weight reduction …
interaction, it is necessary to implement fast data processing and model weight reduction …
[HTML][HTML] One-dimensional convolutional neural networks for low/high arousal classification from electrodermal activity
The rapid identification of arousal is of great interest in various applications such as health
care for the elderly, athletes, drivers and students, among others. Therefore, advanced …
care for the elderly, athletes, drivers and students, among others. Therefore, advanced …
Eeg-based seizure detection using variable-frequency complex demodulation and convolutional neural networks
Epilepsy is a complex neurological disorder characterized by recurrent and unpredictable
seizures that affect millions of people around the world. Early and accurate epilepsy …
seizures that affect millions of people around the world. Early and accurate epilepsy …
Exploring socially shared regulation with an AI deep learning approach using multimodal data
Socially shared regulation of learning (SSRL) is essential for the success of collaborative
learning, yet learners often neglect needed regulation while facing challenges. In order to …
learning, yet learners often neglect needed regulation while facing challenges. In order to …