CyprienQuemeneur/fedpylot

FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of Vehicles

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Emerging

This project helps researchers and enthusiasts explore and simplify federated learning for real-time object detection models, specifically for autonomous driving applications. It takes in existing autonomous driving datasets like KITTI or nuImages and outputs trained object detection models. The end-users are researchers or engineers working on self-driving car technology who need to train detection models collaboratively without sharing raw data.

No commits in the last 6 months.

Use this if you are a researcher in autonomous driving and need a straightforward way to implement and experiment with federated learning for object detection on a high-performance computing (HPC) cluster.

Not ideal if you need advanced compression or privacy-preservation techniques beyond half-precision model updates and hybrid encryption, or if your application isn't focused on real-time object detection for vehicles.

autonomous-driving federated-learning object-detection vehicle-vision AI-research
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 18 / 25

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Stars

50

Forks

15

Language

Jupyter Notebook

License

GPL-3.0

Last pushed

May 19, 2025

Commits (30d)

0

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