A review of uncertainty quantification in deep learning
Uncertainty quantification (UQ) methods play a pivotal role in reducing the impact of uncertainties during both optimization and decision making processes. They […]
Informative Feature Disentanglement 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 […]
Attention-based networks for analyzing inappropriate speech in Arabic text
Analyzing social media posts and comments has become a critical task to prevent cyberbullying and hate speech. In this work we present […]
Application of Deep Learning to Sphere Decoding for Large MIMO Systems
Although the sphere decoder (SD) is a powerful detector for multiple-input multiple-output (MIMO) systems, it has become computationally prohibitive in massive MIMO […]
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 […]