activity
20192021
most citedDeep Joint Transmission-Recognition for Multi-View Cameras

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

cs.IT2021

Federated mmWave Beam Selection Utilizing LIDAR Data

Mahdi Boloursaz Mashhadi, Mikolaj Jankowski, Tze-Yang Tung +2

Efficient link configuration in millimeter wave (mmWave) communication systems is a crucial yet challenging task due to the overhead imposed by beam selection. For vehicle-to-infra…

cs.LG20201 cited

Deep Joint Transmission-Recognition for Multi-View Cameras

Ezgi Ozyilkan, Mikolaj Jankowski

We propose joint transmission-recognition schemes for efficient inference at the wireless edge. Motivated by the surveillance applications with wireless cameras, we consider the pe…

eess.SP2020

Communicate to Learn at the Edge

Deniz Gunduz, David Burth Kurka, Mikolaj Jankowski +3

Bringing the success of modern machine learning (ML) techniques to mobile devices can enable many new services and businesses, but also poses significant technical and research cha…

cs.IT2020

Joint Device-Edge Inference over Wireless Links with Pruning

Mikolaj Jankowski, Deniz Gunduz, Krystian Mikolajczyk

We propose a joint feature compression and transmission scheme for efficient inference at the wireless network edge. Our goal is to enable efficient and reliable inference at the e…

cs.IT2019

Deep Joint Source-Channel Coding for Wireless Image Retrieval

Mikolaj Jankowski, Deniz Gunduz, Krystian Mikolajczyk

Motivated by surveillance applications with wireless cameras or drones, we consider the problem of image retrieval over a wireless channel. Conventional systems apply lossy compres…