29 citations · 32 across the 5 of their papers we have counts for
5 papers
Edge Generation Scheduling for DAG Tasks Using Deep Reinforcement Learning
Binqi Sun, Mirco Theile, Ziyuan Qin +4
Directed acyclic graph (DAG) tasks are currently adopted in the real-time domain to model complex applications from the automotive, avionics, and industrial domains that implement…
Learning to Generate All Feasible Actions
Mirco Theile, Daniele Bernardini, Raphael Trumpp +3
Modern cyber-physical systems are becoming increasingly complex to model, thus motivating data-driven techniques such as reinforcement learning (RL) to find appropriate control age…
6IMPOSE: Bridging the Reality Gap in 6D Pose Estimation for Robotic Grasping
Hongpeng Cao, Lukas Dirnberger, Daniele Bernardini +2
6D pose recognition has been a crucial factor in the success of robotic grasping, and recent deep learning based approaches have achieved remarkable results on benchmarks. However,…
Sigil3D: A Crowdsourcing Platform for Interactive 3D Content
Andrea Barillari, Daniele Bernardini, Pierluigi Crescenzi
In this paper we propose applying the crowdsourcing approach to a software platform that uses a modern and state-of-the-art 3D game engine. This platform could facilitate the gener…
Nonlinear Volterra model of a loudspeaker behavior based on Laser Doppler Vibrometry
Alessandro Loriga, Parvin Moyassari, Daniele Bernardini +3
We demonstrate the capabilities of nonlinear Volterra models to simulate the behavior of an audio system and compare them to linear filters. In this paper a nonlinear model of an a…