activity
20132024
most citedThe Evolution of First Person Vision Methods: A Survey

178 citations · 334 across the 24 of their papers we have counts for

collaborators

26 papers

cs.RO2024

Self-Supervised Path Planning in UAV-aided Wireless Networks based on Active Inference

Ali Krayani, Khalid Khan, Lucio Marcenaro +2

This paper presents a novel self-supervised path-planning method for UAV-aided networks. First, we employed an optimizer to solve training examples offline and then used the result…

eess.SP2024★ 1 cited

Interactive Bayesian Generative Models for Abnormality Detection in Vehicular Networks

Nobel J. William, Ali Krayani, Lucio Marcenaro +1

The following paper proposes a novel Vehicle-to-Everything (V2X) network abnormality detection scheme based on Bayesian generative models for enhanced network self-awareness functi…

eess.SP2023

Intelligent Resource Allocation for UAV-Based Cognitive NOMA Networks: An Active Inference Approach

Felix Obite, Ali Krayani, Atm S. Alam +3

Future wireless networks will need to improve adaptive resource allocation and decision-making to handle the increasing number of intelligent devices. Unmanned aerial vehicles (UAV…

eess.SP2023★ 1 cited

Active Inference for Sum Rate Maximization in UAV-Assisted Cognitive NOMA Networks

Felix Obite, Ali Krayani, Atm S. Alam +3

Given the surge in wireless data traffic driven by the emerging Internet of Things (IoT), unmanned aerial vehicles (UAVs), cognitive radio (CR), and non-orthogonal multiple access…

eess.SP2023★ 2 cited

Integrated Sensing and Communication for Joint GPS Spoofing and Jamming Detection in Vehicular V2X Networks

Ali Krayani, Gabriele Barabino, Lucio Marcenaro +1

Vehicle-to-everything (V2X) communication is expected to be a prominent component of the sixth generation (6G) to accomplish intelligent transportation systems (ITS). Autonomous ve…

cs.LG2022★ 21 cited

A Novel Resource Allocation for Anti-jamming in Cognitive-UAVs: an Active Inference Approach

Ali Krayani, Atm S. Alam, Lucio Marcenaro +2

This work proposes a novel resource allocation strategy for anti-jamming in Cognitive Radio using Active Inference (), and a cognitive-UAV is employed as a case study…