MARVEL MVP Info Day – Insights & Lessons Learned
The 1st MARVEL MVP Info Day was successfully held on January 28th, 2022, virtually hosted by Fondazione Bruno Kessler. And here is the aftermath...
The 1st MARVEL MVP Info Day was successfully held on January 28th, 2022, virtually hosted by Fondazione Bruno Kessler. And here is the aftermath...
Detailed info The Best of Many Worlds: Scheduling Machine Learning Inference on CPU-GPU Integrated Architectures AuthorsRafail Tsirbas, Giorgos Vasiliadis, Sotiris IoannidisTitleThe Best of Many Worlds: Scheduling Machine Learning Inference on…
The last plenary meeting of MARVEL took place on March 21-22, 2022 in a hybrid format with many partners attending physically the meeting in Athens Greece.
Detailed info Responsible AI at the edge: towards privacy-preserving smart cities AuthorsLuca Zanella, Yiming Wang, Nicola Dall'Asen, Alberto Ancilotto, Francesco Paissan, Elisa Ricci, Elisabetta Farella, Alessio Brutti and Marco PistoreTitleResponsible…
Organized by TAU and ATOS, the 1st Benchmarking Workshop of MARVEL took place remotely on January 25, 2022, with more than 30 participants from the 17 organisations of the consortium.
The MARVEL MVP Info Day is an online event for public authorities, Traffic Managers, Law Enforcement Agencies, data scientists, engineers, architects, technical project managers and other people who are focused on smart city technologies, products and services.
On the 16th of December, the first MARVEL Advisory Board meeting was successfully conducted. The meeting was held online. Representatives from all consortium members were present along with the three Advisory Board members.
The latest plenary meeting of MARVEL took place on November 18-19, 2021 in a hybrid format with almost have of the partners meeting face2face in Athens Greece and the other half virtually.
The Machine Learning and Computational Intelligence group at Aarhus University organized a webinar presenting the current research efforts of the group.
A Smart City based on data acquisition, handling and intelligent analysis requires efficient design and implementation of the respective AI technologies and the underlying infrastructure for seamlessly analyzing the large amounts of data in real-time.