Enhancing Computer Vision through Federated Learning

The overall goal of our project is to implement federated learning computer vision related projects such as object detection. The objective is to Develop an object detection model using YOLOv8 and finally Integrate Federated Learning into the object detection system using the Flower framework. Federated Learning is a Distributed Machine Learning technique that enables collaborative training of models without centralizing data. This approach is particularly attractive for privacy-sensitive applications, such as object type detection, where data collection and sharing can be challenging.