Unravelling Peach Leaf Disease Severity: A Federated Learning CNN Perspective
The identification and severity evaluation of peach leaf diseases using Convolutional Neural
Networks (CNN) inside a federated learning (FL) framework is presented in detail in this …
Networks (CNN) inside a federated learning (FL) framework is presented in detail in this …
Insights into multi-model federated learning: An advanced approach for air quality index forecasting
The air quality index (AQI) forecast in big cities is an exciting study area in smart cities and
healthcare on the Internet of Things. In recent years, a large number of empirical, academic …
healthcare on the Internet of Things. In recent years, a large number of empirical, academic …
Apple Leaf Disease Recognition: A Robust Federated Learning CNN Methodology
Apple leaf diseases threaten apple orchard sustain ability and production worldwide.
Accurate and early identification is essential for the successful care and control of many …
Accurate and early identification is essential for the successful care and control of many …
Multichannel aloha optimization for federated learning with multiple models
Large-scale wireless sensor networks are instrumental for several Internet of Things (IoT)
applications involving data analytics and machine learning. The huge data volume …
applications involving data analytics and machine learning. The huge data volume …
Multi-model federated learning with provable guarantees
Federated Learning (FL) is a variant of distributed learning where edge devices collaborate
to learn a model without sharing their data with the central server or each other. We refer to …
to learn a model without sharing their data with the central server or each other. We refer to …
Fair Concurrent Training of Multiple Models in Federated Learning
Federated learning (FL) enables collaborative learning across multiple clients. In most FL
work, all clients train a single learning task. However, the recent proliferation of FL …
work, all clients train a single learning task. However, the recent proliferation of FL …
Federated Learning for Air Quality Index Prediction: An Overview
The air quality index forecast in big cities is an exciting study area in smart cities and
healthcare on the Internet of Things. In recent years, a large number of empirical, academic …
healthcare on the Internet of Things. In recent years, a large number of empirical, academic …
FedAST: Federated Asynchronous Simultaneous Training
Federated Learning (FL) enables edge devices or clients to collaboratively train machine
learning (ML) models without sharing their private data. Much of the existing work in FL …
learning (ML) models without sharing their private data. Much of the existing work in FL …
Flow: A scalable multi-model federated learning framework on the wheels
The highly mobility nature of connected vehicles poses significant challenges in the
research area of federated learning, and to the best of our knowledge, the existing federated …
research area of federated learning, and to the best of our knowledge, the existing federated …
Multi-Head DNN Based Federated Learning for RSRP Prediction in 6G Wireless Communication
M Yu, X Xiong, Z Li, X Xia - IEEE Access, 2024 - ieeexplore.ieee.org
In the realm of wireless communications, accurate Radio Signal Received Power (RSRP)
prediction serves as the foundation for improving user experience and optimizing network …
prediction serves as the foundation for improving user experience and optimizing network …