Depression Recognition using Remote Photoplethysmography from Facial Videos
Depression is a mental illness that may be harmful to an individual’s health. The detection of mental health disorders in the early […]
Federated Learning on the Road Autonomous Controller Design for Connected and Autonomous Vehicles
The deployment of future intelligent transportation systems is contingent upon seamless and reliable operation of connected and autonomous vehicles (CAVs). One key […]
Evolution Toward 6G Multi-band Wireless Networks
In this article we first present the vision key performance indicators key enabling techniques (KETs) and services of 6G wireless networks. Then […]
Communication-Oriented Model Fine-Tuning for Packet-Loss Resilient Distributed Inference Under Highly Lossy IoT Networks
The distributed inference (DI) framework has gained traction as a technique for real-time applications empowered by cutting-edge deep machine learning (ML) on […]
Pain fingerprinting using multimodal sensing
Pain is a complex phenomenon, the experience of which varies widely across individuals. At worst, chronic pain can lead to anxiety and […]
Towards Real-time Learning for Edge-Cloud Continuum with Vehicular Computing
Sensor-driven IoT systems are well-known for their capacity to accelerate massive amounts of data in a comparatively short period of time. To […]
End-to-End Intent-Based Networking
To reap its full benefits, 5G must evolve into a scalable decentralized architecture by exploiting intelligence ubiquitously and securely across different technologies, […]
Connection between the physicochemical characteristics of amorphous carbon thin films and their electrochemical properties
Connecting a material’s surface chemistry with its electrocatalytic performance is one of the major questions in analytical electrochemistry. This is especially important […]
BayGo
This article deals with the problem of distributed machine learning, in which agents update their models based on their local datasets, and […]
A Learning-Based Fast Uplink Grant for Massive IoT via Support Vector Machines and Long Short-Term Memory
The current random access (RA) allocation techniques suffer from congestion and high signaling overhead while serving massive machine type communication (mMTC) applications. […]