Lightweight federated learning for rice leaf disease classification using non independent and identically distributed images

M Aggarwal, V Khullar, N Goyal, A Alammari… - Sustainability, 2023 - mdpi.com
Rice (Oryza sativa L.) is a vital food source all over the world, contributing 15% of the protein
and 21% of the energy intake per person in Asia, where most rice is produced and …

Federated transfer learning for rice-leaf disease classification across multiclient cross-silo datasets

M Aggarwal, V Khullar, N Goyal, R Gautam, F Alblehai… - Agronomy, 2023 - mdpi.com
Paddy leaf diseases encompass a range of ailments affecting rice plants' leaves, arising
from factors like bacteria, fungi, viruses, and environmental stress. Precision agriculture …

f-FNC: Privacy concerned efficient federated approach for fake news classification

V Khullar, HP Singh - Information Sciences, 2023 - Elsevier
Fake news and manipulated information affect the social, economic and emotional growth of
the world's population. For the identification of fake news, several classification systems are …

Federated learning based driver recommendation for next generation transportation system

J Vyas, D Das, S Chaudhury - Expert Systems with Applications, 2023 - Elsevier
Driving behavior analysis benefits the transportation system in terms of road safety,
maintenance costs, vehicle's off-road time, fuel consumption, and enhanced driving …

Digital Twin-Enabled Internet of Vehicles Applications

J Gao, C Peng, T Yoshinaga, G Han, S Guleng, C Wu - Electronics, 2024 - mdpi.com
The digital twin (DT) paradigm represents a groundbreaking shift in the Internet of Vehicles
(IoV) landscape, acting as an instantaneous digital replica of physical entities. This synthesis …

A lane-changing trajectory re-planning method considering conflicting traffic scenarios

H Du, Y Sun, Y Pan, Z Li, P Siarry - Engineering Applications of Artificial …, 2024 - Elsevier
An essential aspect of intelligent driving systems is the automatic lane-changing function.
However, in real-world traffic situations, the initially planned lane-changing trajectory can …

Securing Tomorrow's Smart Cities: Investigating Software Security in Internet of Vehicles and Deep Learning Technologies

R Jain, N Tihanyi, MA Ferrag - arXiv preprint arXiv:2407.16410, 2024 - arxiv.org
Integrating Deep Learning (DL) techniques in the Internet of Vehicles (IoV) introduces many
security challenges and issues that require thorough examination. This literature review …

Afm3d: An asynchronous federated meta-learning framework for driver distraction detection

S Liu, L You, R Zhu, B Liu, R Liu, H Yu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Driver Distraction Detection (3D) is of great significance in helping intelligent vehicles
decide whether to remind drivers or take over the driving task and avoid traffic accidents …

Resource-aware multi-criteria vehicle participation for federated learning in Internet of vehicles

J Wen, J Zhang, Z Zhang, Z Cui, X Cai, J Chen - Information Sciences, 2024 - Elsevier
Federated learning (FL), as a safe distributed training mode, provides strong support for the
edge intelligence of the Internet of Vehicles (IoV) to realize efficient collaborative control and …

[HTML][HTML] An intelligent FL-based vehicle route optimization protocol for green and sustainable IoT connected IoV

P Narsimhulu, P Chithaluru, F Al-Turjman, V Guda… - Internet of Things, 2024 - Elsevier
Abstract The intelligent Internet of Vehicles (IoV) provides superior results in effectively
addressing complex transportation challenges. Predicting vehicle traffic, crashes, demand …