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Evaluation of oil workers' performance based on surveillance video

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Department of Information Technologies

DOI

https://doi.org/10.1109/SIBIRCON48586.2019.8958352
Final published version

Elena Lebedeva
Andrey Zubkov
Denis Bondarenko
Konstantin Rymarenko
Marat Nukhaev
Sergey Grishchenko

Original language	English
Title of host publication	SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	432-435
Number of pages	4
ISBN (Electronic)	9781728144016
DOIs	https://doi.org/10.1109/SIBIRCON48586.2019.8958352
Publication status	Published - Oct 2019
Event	2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019 - Novosibirsk, Russian Federation Duration: 21 Oct 2019 → 27 Oct 2019

Publication series

Name	SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings

Conference

Conference	2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019
Country/Territory	Russian Federation
City	Novosibirsk
Period	21.10.2019 → 27.10.2019

OECD FOS+WOS

1.02 COMPUTER AND INFORMATION SCIENCES

Research areas

ArUco, computer vision, convolutional neural networks, CTPN, Faster R-CNN, fiducial markers, OCR, RUNETag, single-shot detectors, surveillance, Tesseract, uniform numbers, workers' performance

ID: 28286594