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001-es BibID:	BIBFORM102588
035-os BibID:	(WoS)000845243900001 (Scopus)85133535530
Első szerző:	Kapusi Tibor Péter (mérnökinformatikus, villamosmérnök)
Cím:	Application of Deep Learning in the Deployment of an Industrial SCARA Machine for Real-Time Object Detection / Tibor Péter Kapusi, Timotei István Erdei, Géza Husi, András Hajdu
Dátum:	2022
ISSN:	2218-6581
Megjegyzések:	In the spirit of innovation, the development of an intelligent robot system incorporating the basic principles of Industry 4.0 was one of the objectives of this study. With this aim, an experimental application of an industrial robot unit in its own isolated environment was carried out using neural networks. In this paper, we describe one possible application of deep learning in an Industry 4.0 environment for robotic units. The image datasets required for learning were generated using data synthesis. There are significant benefits to the incorporation of this technology, as old machines can be smartened and made more efficient without additional costs. As an area of application, we present the preparation of a robot unit which at the time it was originally produced and commissioned was not capable of using machine learning technology for object-detection purposes. The results for different scenarios are presented and an overview of similar research topics on neural networks is provided. A method for synthetizing datasets of any size is described in detail. Specifically, the working domain of a given robot unit, a possible solution to compatibility issues and the learning of neural networks from 3D CAD models with rendered images will be discussed.
Tárgyszavak:	Műszaki tudományok Gépészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk cyber-physical systems Industry 4.0 SCARA robot deep learning YOLO
Megjelenés:	Robotics. - 11 : 4 (2022), p. 1-20. -
További szerzők:	Erdei Timotei István (1990-) (mechatronikai mérnök) Husi Géza (1962-) (gépészmérnök, mechatronikai mérnök, számítógépes tervezőmérnök) Hajdu András (1973-) (matematikus, informatikus)
Pályázati támogatás:	TKP2020-NKA-04 Egyéb
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat DOI Szerző által megadott URL
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