19/04/2022: TS. Nguyễn Chí Thành (AMST, Hà Nội), CRF-EfficientUNet: An Improved UNet Framework for Polyp Segmentation in Colonoscopy Images

Due to its communication efficiency and privacy-preserving capability, federated learning has emerged as a promising framework for machine learning in 5G-and-beyond wireless networks. Therefore, the novel designs of wireless networks to support the stable and fast operation of federated learning are of great interest. This talk will first highlight the reasons why federated learning becomes important in the future, briefly introduce communication- oriented research directions for realizing federated learning in wireless networks and then discuss state-of-the-art solutions for a massive multiple-input multiple-output (MIMO) network to efficiently support federated learning.

Speaker: TS. Nguyễn Chí Thành, AMST, Hà Nội

Time: 15:30, Tuesday, April 19, 2022

Venue: Webinar