Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data

Short summary

Federated learning enables drones to collaborate on improving object detection models while keeping image data local and private. Researchers tested this on the KIIT-MiTA dataset using Sherpa.ai, achieving 67.8% performance gains versus single-drone training while matching centralized approaches. This enables privacy-preserving, scalable perception for distributed drone fleets without centralizing sensitive aerial imagery.

• •Federated learning allows distributed drones to train shared object detection models without centralizing image data
• •Sherpa.ai implementation achieved 67.8% relative performance improvement over single-drone baseline on KIIT-MiTA dataset
• •Enables privacy-preserving, scalable perception for drone fleets suitable even for limited edge infrastructure

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