5 papers
When Quantum Federated Learning Meets Blockchain in 6G Networks
Dinh C. Nguyen, Md Bokhtiar Al Zami, Ratun Rahman +3
Quantum federated learning (QFL) is emerging as a key enabler for intelligent, secure, and privacy-preserving model training in next-generation 6G networks. By leveraging the compu…
A Joint Reconstruction-Triplet Loss Autoencoder Approach Towards Unseen Attack Detection in IoV Networks
Julia Boone, Tolunay Seyfi, Fatemeh Afghah
Internet of Vehicles (IoV) systems, while offering significant advancements in transportation efficiency and safety, introduce substantial security vulnerabilities due to their hig…
DiSa: Directional Saliency-Aware Prompt Learning for Generalizable Vision-Language Models
Niloufar Alipour Talemi, Hossein Kashiani, Hossein R. Nowdeh +1
Prompt learning has emerged as a powerful paradigm for adapting vision-language models such as CLIP to downstream tasks. However, existing methods often overfit to seen data, leadi…
Role of flow topology in wind-driven wildfire propagation
Siva Viknesh, Ali Tohidi, Fatemeh Afghah +2
Wildfires propagate through intricate interactions between wind, fuel, and terrain, resulting in complex behaviors that pose challenges for accurate predictions. This study investi…
FlameFinder: Illuminating Obscured Fire through Smoke with Attentive Deep Metric Learning
Hossein Rajoli, Sahand Khoshdel, Fatemeh Afghah +1
FlameFinder is a deep metric learning (DML) framework designed to accurately detect flames, even when obscured by smoke, using thermal images from firefighter drones during wildfir…