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Authors: Alexey Kolker 1 ; Sofia Oshchepkova 1 ; Zhanna Pershina 1 ; Lubomir Dimitrov 2 ; Vladislav Ivanov 2 ; Aquib Rashid 3 and Mohamad Bdiwi 3

Affiliations: 1 Faculty of Automation, Novosibirsk State Technical University, Novosibirsk, Russia ; 2 Department for Machine Elements and Non-Metallic Constructions, Technical University of Sofia, Sofia, Bulgaria ; 3 Robot System Department, Fraunhofer Institute for Machine Tools and Forming Technology, Chemnitz, Germany

Keyword(s): POV-Ray, Ray Tracing, COCO-style Annotation, Instance Segmentation, Convolutional Neural Network, Robotics, Computer Vision.

Abstract: Creating quality-annotated dataset is one of the main tasks in the field of deep learning technologies for pattern recognition. However, in the real world, collecting a sufficient number of detailed images of an object is difficult and time-consuming. The article considers an approach to creating synthetic datasets based on the ray tracing method. This paper also presents the results of success tests of real object image segmentation by convolutional neural networks, trained entirely on synthetic data and data of different nature.

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Paper citation in several formats:
Kolker, A.; Oshchepkova, S.; Pershina, Z.; Dimitrov, L.; Ivanov, V.; Rashid, A. and Bdiwi, M. (2020). The Ray Tracing based Tool for Generation Artificial Images and Neural Network Training. In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - KMIS; ISBN 978-989-758-474-9; ISSN 2184-3228, SciTePress, pages 257-264. DOI: 10.5220/0010168102570264

@conference{kmis20,
author={Alexey Kolker. and Sofia Oshchepkova. and Zhanna Pershina. and Lubomir Dimitrov. and Vladislav Ivanov. and Aquib Rashid. and Mohamad Bdiwi.},
title={The Ray Tracing based Tool for Generation Artificial Images and Neural Network Training},
booktitle={Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - KMIS},
year={2020},
pages={257-264},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010168102570264},
isbn={978-989-758-474-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - KMIS
TI - The Ray Tracing based Tool for Generation Artificial Images and Neural Network Training
SN - 978-989-758-474-9
IS - 2184-3228
AU - Kolker, A.
AU - Oshchepkova, S.
AU - Pershina, Z.
AU - Dimitrov, L.
AU - Ivanov, V.
AU - Rashid, A.
AU - Bdiwi, M.
PY - 2020
SP - 257
EP - 264
DO - 10.5220/0010168102570264
PB - SciTePress

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