Comparation of Federated and Centralized Learning for Image Classification

• DOI: 10.33558/piksel.v11i2.7367
• Publication Date: 2023-10-03T06:16:06Z
• Authors: Farhanna Mar'i; Ahmad Afif Supianto; Fitra Abdurrachma...
• Keywords: MNIST database; Federated Learning; Contextual image classification

Federated Learning (FL) is a new approach in machine learning or it can also be called collaborative learning, which method that includes client devices to carry out the training process, so clients do not need send data server but directly conduct on their respective devices. respectively. The models generated from local will sent for further global aggregation. Therefore, FL referred as maintain privacy of owner, because submitted and still stored each client's device. In this study, performance comparison carried prove whether latest Learning, produce same accuracy traditional approach, Centralized Machine case Image Classification. two approaches would conducted by using Open Source Classification dataset, namely MNIST. presented evaluation Accuracy. result shows almost overcome provided Accuracy 76%.