Lightweight federated learning for rice leaf disease classification using non independent and identically distributed images
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 …
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
Paddy leaf diseases encompass a range of ailments affecting rice plants' leaves, arising
from factors like bacteria, fungi, viruses, and environmental stress. Precision agriculture …
from factors like bacteria, fungi, viruses, and environmental stress. Precision agriculture …
f-FNC: Privacy concerned efficient federated approach for fake news classification
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 …
the world's population. For the identification of fake news, several classification systems are …
Federated learning based driver recommendation for next generation transportation system
Driving behavior analysis benefits the transportation system in terms of road safety,
maintenance costs, vehicle's off-road time, fuel consumption, and enhanced driving …
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 …
(IoV) landscape, acting as an instantaneous digital replica of physical entities. This synthesis …
A lane-changing trajectory re-planning method considering conflicting traffic scenarios
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 …
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
Integrating Deep Learning (DL) techniques in the Internet of Vehicles (IoV) introduces many
security challenges and issues that require thorough examination. This literature review …
security challenges and issues that require thorough examination. This literature review …
Afm3d: An asynchronous federated meta-learning framework for driver distraction detection
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 …
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 …
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
Abstract The intelligent Internet of Vehicles (IoV) provides superior results in effectively
addressing complex transportation challenges. Predicting vehicle traffic, crashes, demand …
addressing complex transportation challenges. Predicting vehicle traffic, crashes, demand …