5 accepted papers
Deep learning (DL) techniques are increasingly used for diagnosing Parkinsons Disease (PD) due to their non-invasive nature and accessibility. This study introduces PD-VOST (Parkinsons Disease Voice Spectrogram Transformer), an innovative DL model that employs the Transformer architecture for PD dia…
We delve into the issue of node classification within graphs, specifically reevaluating the concept of neighborhood aggregation, which is a fundamental component in graph neural networks (GNNs). Our analysis reveals conceptual flaws within certain benchmark GNN models when operating under the assump…
The integration of Multi-Rotor Aerial Vehicles (MRAVs) into 5G and 6G networks enhances coverage, connectivity, and congestion management. This fosters communication-aware robotics, exploring the interplay between robotics and communications, but also makes the MRAVs susceptible to malicious attacks…
Recently, Supervised Contrastive Learning (SCL) has been shown to significantly outperform the well-known cross-entropy loss-based learning on most classification tasks. In SCL, a neural network is trained to optimize two objectives: pull an anchor and positive samples together in the embedding spac…
We consider the issue of designing closed 3D UAV trajectories that allow for an energy efficient collection of data with a UAV-aided wireless sensor network. We consider a 3D wireless channel model and a realistic dynamical model for the UAV. The proposed trajectory is largely derived analytically,…