E-VAT: An Asymmetric End-to-End Approach to Visual Active Exploration and Tracking

Autor:	Alberto Dionigi, Alessandro Devo, Leonardo Guiducci, Gabriele Costante
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	Human-Computer Interaction reinforcement learning Control and Optimization Artificial Intelligence Control and Systems Engineering Mechanical Engineering Biomedical Engineering deep learning for visual perception Computer Vision and Pattern Recognition Visual tracking Computer Science Applications
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9d3148e65a6682e96f2261a49f4b740 https://hdl.handle.net/11391/1536013 Zobrazit plný text záznamu