Detail of the student project

Topic:Super-resolution for satellite imagery using generative adversial networks
Department:Katedra kybernetiky
Supervisor:Ing. Michal Reinštein Ph.D.
Announce as:DP,BP,PMI,PRO
Description:The aim is to design, implement, and experimentally evaluate deep neural network architecture for solving the problem of increasing resolution (super-resolution) of satellite imagery using Generative Adversial Networks. The contribution will be focused on evaluating the reliability of generated high frequency content that is unobservable in the imagery otherwise. Main tools will be: python and tensorflow.
Responsible person: Petr Pošík