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 […]
Adversarial learning and decomposition-based domain generalization for face anti-spoofing
Face anti-spoofing (FAS) plays a critical role in the face recognition community for securing the face presentation attacks. Many works have been […]
Deep ladder reconstruction-classification network for unsupervised domain adaptation
Unsupervised Domain Adaptation aims to learn a classifier for an unlabeled target domain by transferring knowledge from a labeled source domain. Most […]
Joint Clustering and Discriminative Feature Alignment for Unsupervised Domain Adaptation
Unsupervised Domain Adaptation (UDA) aims to learn a classifier for the unlabeled target domain by leveraging knowledge from a labeled source domain […]
Morphology-preserving reconstruction of times series with missing data for enhancing deep learning-based classification
There is a growing concern among deep learning-based decoding methods used for biomedical time series. In small dataset particularly those that rely […]