STT-Net: Simplified Temporal Transformer for Emotion Recognition
M Khan, A El Saddik, M Deriche, W Gueaieb - IEEE Access, 2024 - ieeexplore.ieee.org
Emotion recognition is one of the crucial topics in computer vision to efficiently recognize the
expression of humans through faces. Recently, transformers have been recognized as a …
expression of humans through faces. Recently, transformers have been recognized as a …
Graph reasoning and Inception attention network for dermoscopy segmentation
T Cheng - Biomedical Signal Processing and Control, 2024 - Elsevier
Precise segmentation of lesions from dermoscopy images is an essential task in computer-
aided surgical planning. Unlike current methods that often concentrate on attention …
aided surgical planning. Unlike current methods that often concentrate on attention …
A parameter-adaptive spectral graph wavelet transform method for wind turbines vibration signal denoising
J Liu, Q Zhang, D Li, Y Teng, S Wu, X Wang - International Journal of …, 2024 - Elsevier
The signal noise can have a negative impact on the accuracy of engineering equipment
condition assessment. However, the choice of decomposition layers and design parameters …
condition assessment. However, the choice of decomposition layers and design parameters …
Algorithm for drowsiness detection based on hybrid brain network parameter optimization
K Zhang, D Wu, Q Liu, F Dong, J Liu, L Jiang… - … Signal Processing and …, 2024 - Elsevier
Drowsiness detection is a test designed to detect a person's reaction ability and speed while
in a state of fatigue. This type of drowsiness detection has many practical applications in …
in a state of fatigue. This type of drowsiness detection has many practical applications in …
Automated ABR and MMN extraction using a customized headband for hearing screening
RK Joshi, KS Manu, RS Hari, A Krishnan… - … Signal Processing and …, 2024 - Elsevier
Objective Stimuli-elicited EEG responses, known as Event-Related Potentials (ERPs), reflect
the health status of underlying electrophysiological processes and are frequently used for …
the health status of underlying electrophysiological processes and are frequently used for …
Investigating the Influence of Driving on Brain Connectivity Networks and Emotion Processing Mechanism Based on EEG Signals
G Li, L Zhang, C Li, Z Li, F Gao, L Zheng… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Humans are frequently driving with different emotions, but how driving affects human's brain
information processing mechanism in different emotional states is still unknown. In this …
information processing mechanism in different emotional states is still unknown. In this …
Deep Diffusion for Training Chatter Detection Systems for Machine Tools
PH Kuo, HH Wu, HT Yau - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
In machine tool operations, chatter can cause machining errors and reduce a tool's lifespan
and the production quality, and artificial intelligence is commonly used for predicting …
and the production quality, and artificial intelligence is commonly used for predicting …
Analyzing lower body movements using machine learning to classify autistic children
SMS Aljabiri, MM Hamdan - Biomedical Signal Processing and Control, 2024 - Elsevier
Autism spectrum disorder is a neurological disorder that affects children at an early age and
its symptoms appear in varying degrees. Early detection of ASD and follow-up of treatment …
its symptoms appear in varying degrees. Early detection of ASD and follow-up of treatment …
Schizophrenia Detection using Interconnected Graph Based Features from EEG Signals
R Sharma, HK Meena - IEEE Transactions on Instrumentation …, 2024 - ieeexplore.ieee.org
Schizophrenia (Sz) is a complex mental disorder characterized by disruptions in thought
processes, perceptions, and emotional regulation. It is imperative to identify schizophrenia at …
processes, perceptions, and emotional regulation. It is imperative to identify schizophrenia at …