Name: Teodora Selea
Affiliation: West University of Timisoara
Primary research interest: Machine Learning applied on Earth Observation
Title of the lecture: Deep Learning Applied to Earth Observation
Keywords: eep learning, earth observation, agriculture
Summary: The growing availability of high-resolution Earth Observation (EO) data made it necessary to monitor and analyse the environment on a wide scale. Deep learning techniques have showed a lot of potential for getting structured information out of EO images. This opens up a lot of possibilities, from classifying land cover to precision agriculture. This talk gives an overview of the main problems and methods involved in getting EO datasets ready for deep learning processes. The examples used are from agricultural monitoring, however the methods talked about can be used in many EO-driven applications. The goal of this presentation is to give a structured view on how to create strong and scalable deep learning models for EO.