Abstract: We propose a novel communication design, termed random orthogonalization, for federated learning (FL) in a massive multiple-input and multiple-output (MIMO) wireless system. The key novelty ...

Abstract: Person re-identification aims to identify whether pairs of images belong to the same person or not. This problem is challenging due to large differences in camera views, lighting and ...

We comprehensively evaluate unORANIC+ in terms of reconstruction quality, capability to revise existing corruptions, corruption robustness, and its effectiveness in downstream tasks such as disease ...

We introduce unORANIC, an unsupervised approach that uses an adapted loss function to drive the orthogonalization of anatomy and image-characteristic features. The method is versatile for diverse ...