30 citations · 33 across the 10 of their papers we have counts for
10 papers
Meta Reinforcement Learning for Strategic IoT Deployments Coverage in Disaster-Response UAV Swarms
Marwan Dhuheir, Aiman Erbad, Ala Al-Fuqaha
In the past decade, Unmanned Aerial Vehicles (UAVs) have grabbed the attention of researchers in academia and industry for their potential use in critical emergency applications, s…
Empowering HWNs with Efficient Data Labeling: A Clustered Federated Semi-Supervised Learning Approach
Moqbel Hamood, Abdullatif Albaseer, Mohamed Abdallah +1
Clustered Federated Multitask Learning (CFL) has gained considerable attention as an effective strategy for overcoming statistical challenges, particularly when dealing with non in…
Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally
Shawqi Al-Maliki, Adnan Qayyum, Hassan Ali +5
Deep Neural Networks (DNNs) have been the driving force behind many of the recent advances in machine learning. However, research has shown that DNNs are vulnerable to adversarial…
R2S100K: Road-Region Segmentation Dataset For Semi-Supervised Autonomous Driving in the Wild
Muhammad Atif Butt, Hassan Ali, Adnan Qayyum +3
Semantic understanding of roadways is a key enabling factor for safe autonomous driving. However, existing autonomous driving datasets provide well-structured urban roads while ign…
Fair Selection of Edge Nodes to Participate in Clustered Federated Multitask Learning
Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha +3
Clustered federated Multitask learning is introduced as an efficient technique when data is unbalanced and distributed amongst clients in a non-independent and identically distribu…
Can We Revitalize Interventional Healthcare with AI-XR Surgical Metaverses?
Adnan Qayyum, Muhammad Bilal, Muhammad Hadi +5
Recent advancements in technology, particularly in machine learning (ML), deep learning (DL), and the metaverse, offer great potential for revolutionizing surgical science. The com…