Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning
Accurate automated medical image recognition, including classification and segmentation, is one of the most challenging tasks in medical image analysis. Recently, deep […]
Deep Ladder-Suppression Network for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) aims at learning a classifier for an unlabeled target domain by transferring knowledge from a labeled source domain […]
Vision-based Fall Detection using Body Geometry?
Falling is a major health problem that causes thousands of deaths every year, according to the World Health Organization. Fall detection and […]
Micro-expression action unit detection with spatial and channel attention
Action Unit (AU) detection plays an important role in facial behaviour analysis. In the literature, AU detection has extensive researches in macro-expressions. […]
Fall Detection using Body Geometry in Video Sequences
According to the World Health Organization, falling of the elderly is a major health problem that causes many injuries and thousands of […]
Joint Local and Global Information Learning With Single Apex Frame Detection for Micro-Expression Recognition
Micro-expressions (MEs) are rapid and subtle facial movements that are difficult to detect and recognize. Most recent works have attempted to recognize […]
A Correlation-Driven Mapping For Deep Learning application in detecting artifacts within the EEG
Objective: When developing approaches for automatic preprocessing of electroencephalogram (EEG) signals in non-isolated demanding environment such as intensive care unit (ICU) or […]
A Multi-Stream Feature Fusion Approach for Traffic Prediction
Accurate and timely traffic flow prediction is crucial for intelligent transportation systems (ITS). Recent advances in graph-based neural networks have achieved promising […]
Gender Identification from Arabic Speech Using Machine Learning
Speech recognition is becoming increasingly used in real-world applications. One of the interesting applications is automatic gender recognition which aims to recognize […]
A Deep Multiscale Spatiotemporal Network for Assessing Depression from Facial Dynamics
Recently deep learning models have been successfully employed in video-based affective computing applications. One key application is automatic depression recognition from facial […]