Deep Learning for Autonomous Systems and Smart Cities

Deep Learning for Autonomous Systems and Smart Cities

A Summer School byAarhus University

Almost everything we hear about Artificial Intelligence today is thanks to machine learning (ML) and especially ML algorithms following the end-to-end learning paradigm, which is commonly associated with a type of models referred to as Deep Learning. Deep learning has developed into a mature technology and it is nowadays an essential part in systems that require high-level perception capabilities, such as autonomous vehicles, robots that sense their environment, and multi-modal monitoring systems in smart cities. While successful solutions already exist for a number of research problems, the adoption of high-performing deep learning models in everyday life applications setting restrictions such as level of autonomy, computational power, and memory size, and real-time continuous operation, requires new advancements in both fundamental research and technology. Such research lies at the intersection of two H2020 Research and Innovation projects which jointly organize this summer school with prominent invited speakers and hands-on sessions on related tools and state-of-the-art technologies.

A Collaboration between MARVEL and OpenDR

The OpenDR project is focused on developing a modular, open and non-proprietary toolkit for core robotic functionalities by harnessing deep learning to provide advanced perception and cognition capabilities, meeting in this way the general requirements of robotics applications in various applications areas, such as healthcare, agri-food, and agile production. To this end, OpenDR is developing state-of-the-art lightweight and high resolution-enabled deep learning methods for core robotic functionalities, while investigating ways to integrate perception and action through active perception approaches.

The MARVEL project is focused on novel methods, approaches and engineering paradigms in multimodal audio-visual data management and processing for smart city environments, showcasing the potential to address civic challenges very effectively, from increasing public safety and security to analyzing traffic flows and traffic behavior. To this end, MARVEL is developing a framework to achieve multimodal perception and intelligence for audio-visual scene recognition, event detection and situational awareness without violating ethical and privacy limits.

The summer school will host invited talks by distinguished researchers and industrial experts, as well as talks by the project participants that will reflect the achievements in the two ongoing projects.


23-26 May 2023


INCUBA Store Auditorium (building 5510, room 103) Åbogade 15 8200 Aarhus C Denmark


Official Summer School Landing Page

Things To Know

Register Now to the Deep Learning for Autonomous Systems and Smart Cities Summer School


Organising Committee

Alexandros Iosifidis (OpenDR & MARVEL),
Anastasios Tefas (OpenDR),
Sotirios Ioannidis (MARVEL),

Key Facts

  • Project Coordinator: Dr. Sotiris Ioannidis
  • Institution: Foundation for Research and Technology Hellas (FORTH)
  • E-mail: marvel-info{at} 
  • Start: 01.01.2021
  • Duration: 36 months
  • Participating Organisations: 17
  • Number of countries: 12

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This project has received funding from the European Union’s Horizon 2020 Research and Innovation program under grant agreement No 957337. The website reflects only the view of the author(s) and the Commission is not responsible for any use that may be made of the information it contains.