lambdavi/SatDrive-SegFL
MLDL '23 Project: Federated Learning and Semantic Segmentation for Autonomous Driving and Satellite Images Segmentation
This project helps machine learning researchers explore and compare different methods for image segmentation tasks, particularly in autonomous driving and satellite imagery analysis. It takes raw image datasets (like those from autonomous vehicles or aerial photos) and outputs segmented images, highlighting different objects or regions. This is useful for researchers and engineers developing computer vision models for these specific domains.
Use this if you are a machine learning researcher or engineer experimenting with federated learning and semantic segmentation techniques for autonomous driving or satellite image analysis.
Not ideal if you are a practitioner looking for an out-of-the-box solution to directly apply image segmentation without delving into model architecture or training specifics.
Stars
7
Forks
4
Language
Python
License
GPL-3.0
Last pushed
Jan 21, 2026
Commits (30d)
0
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