Deep Learning for Micro-Expression Recognition
Micro-expressions (MEs) are involuntary facial movements revealing people’s hidden feelings in high-stake situations and have practical importance in various fields. Early methods […]
Importance-Aware Information Bottleneck Learning Paradigm for Lip Reading
Lip reading is the task of decoding text from speakers’ mouth movements. Numerous deep learning-based methods have been proposed to address this […]
Uncertainty-Guided Semi-Supervised Few-Shot Class-Incremental Learning With Knowledge Distillation
Class-Incremental Learning (CIL) aims at incrementally learning novel classes without forgetting old ones. This capability becomes more challenging when novel tasks contain […]
Deep Learning Based Over-the-Air Channel Estimation Using a ZYNQ SDR Platform
Deep learning based channel estimation techniques have recently found an overwhelming interest owing to data-driven learning-based adaptability compared to conventional estimation techniques […]
A Novel Time-Aware Food Recommender-System Based on Deep Learning and Graph Clustering
Food recommender-systems are considered an effective tool to help users adjust their eating habits and achieve a healthier diet. This paper aims […]
Facial Kinship Verification
The goal of Facial Kinship Verification (FKV) is to automatically determine whether two individuals have a kin relationship or not from their […]
Deep Learning for Massive MIMO Uplink Detectors
Detection techniques for massive multiple-input multiple-output (MIMO) have gained a lot of attention in both academia and industry. Detection techniques have a […]
Deep Learning for GPS Spoofing Detection in Cellular-Enabled UAV Systems
Cellular-based Unmanned Aerial Vehicle (UAV) systems are a promising paradigm to provide reliable and fast Beyond Visual Line of Sight (BVLoS) communication […]
Energy-Efficient Model Compression and Splitting for Collaborative Inference Over Time-Varying Channels
Today’s intelligent applications can achieve high performance accuracy using machine learning (ML) techniques, such as deep neural networks (DNNs). Traditionally, in a […]
Deep Neural Network-Based Blind Multiple User Detection for Grant-free Multi-User Shared Access
Multi-user shared access (MUSA) is introduced as advanced code domain non-orthogonal complex spreading sequences to support a massive number of machine-type communications […]