Development and testing of ADAS is largely based on models simulations, but real data are indispensable for many reasons – to determine the relevant scenarios, establish a connection between results simulations situation course as elements set up realistic models. Using data, however, not trivial, all informative, even extensive sets often incomplete. Indeed, automatically information, richness...

Abstract Meta-learning, or learning to learn, is a machine approach that utilizes prior experiences expedite the process on unseen tasks. As data-driven approach, meta-learning requires meta-features represent primary tasks datasets, and are estimated traditonally as engineered dataset statistics require expert domain knowledge tailored for every meta-task. In this paper, first, we propose meta...

Research in Simultaneous Localization and Mapping (SLAM) has made outstanding progress over the past years. SLAM systems are nowadays transitioning from academic to real world applications. However, this transition posed new demanding challenges terms of accuracy robustness. To develop that can address these challenges, datasets containing cutting-edge hardware realistic scenarios required. We ...