Automatic machine learning algorithms have to do the job and to be able to detect important events and objects in real time to allow quick response in tactical environments.

Objectives
A Remote Sensing Image Analyst deals with large amounts of optical and radar remote sensing images. This course presents an overview of the main techniques and technologies necessary to achieve this objective in a context of big data.

Pre-requisites
Mathematics (basic algebra), basic signal processing theory and techniques, computer programming.

This programme is focused on:

• Professionals working in Defence and AeroSpace Industry (up-skilling and re-skilling activities)

IMPORTANT: This prototype programme is EXCLUSIVE FOR partners of the ASSETs+ consortium and associated stakeholders. If you want to join the ASSETs+ Stakeholders Group and become part of our ecosystem, please, click here.

Learning outcomes:

• Differences of the quality factors and features of optical and radar remote sensing images
• Deep knowledge of recent and relevant techniques for massively processing images
• To develop algorithms and systems for reformatting remote sensing images in an efficient way using compressive sensing
• Capability to develop and evaluate machine-learning techniques and to design big data learning systems
• To develop algorithms and systems for automatic clustering