Deep learning automated data analysis of security infrared cameras

dc.contributor.author	Momot, Andrii
dc.contributor.author	Skladchykov, Ivan
dc.date.accessioned	2021-05-19T08:49:47Z
dc.date.available	2021-05-19T08:49:47Z
dc.date.issued	2021
dc.description.abstracten	Prospects for the use of thermal imaging systems in safety control problems are considered. Particularly rel-evant is the timely detection of prohibited items, a potential attacker can hide under clothes. In order to increase the efficiency of thermal imaging security systems, automation thermograms processing using deep learning. In particular, one of the most promising methods is the use of convolutional neural networks for automatic detection of objects in infrared images. The network architecture proposed in article makes it possible to detect identity of prohibited items and to recognize these items with correct answers on the test set up to 97.92%.	uk
dc.format.pagerange	P. 13-16	uk
dc.identifier.citation	Momot, A. Deep learning automated data analysis of security infrared cameras / A. Momot, I. Skladchykov // Slovak international scientific journal. – 2021. – №52. – P. 13–16.	uk
dc.identifier.issn	5782-5319
dc.identifier.uri	https://ela.kpi.ua/handle/123456789/41061
dc.language.iso	en	uk
dc.source	Slovak international scientific journal, №52	uk
dc.subject	thermal testing	uk
dc.subject	infrared cameras	uk
dc.subject	deep learning	uk
dc.subject	convolutional networks	uk
dc.title	Deep learning automated data analysis of security infrared cameras	uk
dc.type	Article	uk

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