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pro vyhledávání: '"Antonella Barisic"'
In this paper a vision-based system for detection, motion tracking and following of Unmanned Aerial Vehicle (UAV) with other UAV (follower) is presented. For detection of an airborne UAV we apply a convolutional neural network YOLO trained on a colle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92fff225886fd9a0578d6366b01129ce
In this letter, we propose a novel approach to generate a synthetic aerial dataset for application in UAV monitoring. We propose to accentuate shape-based object representation by applying texture randomization. A diverse dataset with photorealism in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f3762bf62f0117b568416d4d7e17142
https://doi.org/10.1109/lra.2022.3147337
https://doi.org/10.1109/lra.2022.3147337
Autor:
Antonella Barisic, Marlan Ball, Noah Jackson, Riley McCarthy, Nasib Naimi, Luca Strassle, Jonathan Becker, Maurice Brunner, Julius Fricke, Lovro Markovic, Isaac Seslar, David Novick, Jonathan Salton, Roland Siegwart, Stjepan Bogdan, Rafael Fierro
With the rapid development of technology and the proliferation of uncrewed aerial systems (UAS), there is an immediate need for security solutions. Toward this end, we propose the use of a multi-robot system for autonomous and cooperative counter-UAS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f29055783b42fe08efc813831ae8bef
https://www.bib.irb.hr/1256223
https://www.bib.irb.hr/1256223