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Authors: Oleg Saprykin 1 ; Alexander Fedoseev 1 and Tatyana Mikheeva 2

Affiliations: 1 Samara State Aerospace University, Russian Federation ; 2 Samara State Aerospace University and Scientific and Production Centre «Intelligent Transportation Systems», Russian Federation

Keyword(s): Convolutional Neural Networks, Deep Machine Learning, Hyperspectral Images, Transport Infrastructure, Image Recognition.

Related Ontology Subjects/Areas/Topics: Energy and Economy ; Energy-Aware Systems and Technologies ; Geographic Information Systems (GIS)

Abstract: Actualization of vector maps of the urban transport infrastructure, including street and road network, in conditions of constant changes is a resource-consuming task and it requires the automation of the process. The article considers the solving of problem of transport infrastructure objects recognition in hyperspectral images by deep convolutional neural networks. The hyperspectral images from different sources are considered for solving the problem. We propose a new approach to the formation of receptive fields of convolutional neural networks: the receptive field covers several pixels, but the depth of the colour channels is limited. In the proposed approach the receptive field moves in three dimensions in two spatial dimensions and in spectral channels dimension. It gives the ability to recognize the transport infrastructure objects by spatial patterns and spectrum.

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Paper citation in several formats:
Saprykin, O.; Fedoseev, A. and Mikheeva, T. (2016). Recognition of Urban Transport Infrastructure Objects Via Hyperspectral Images. In Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-185-4; ISSN 2184-495X, SciTePress, pages 203-208. DOI: 10.5220/0005901902030208

@conference{vehits16,
author={Oleg Saprykin. and Alexander Fedoseev. and Tatyana Mikheeva.},
title={Recognition of Urban Transport Infrastructure Objects Via Hyperspectral Images},
booktitle={Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2016},
pages={203-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005901902030208},
isbn={978-989-758-185-4},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - Recognition of Urban Transport Infrastructure Objects Via Hyperspectral Images
SN - 978-989-758-185-4
IS - 2184-495X
AU - Saprykin, O.
AU - Fedoseev, A.
AU - Mikheeva, T.
PY - 2016
SP - 203
EP - 208
DO - 10.5220/0005901902030208
PB - SciTePress

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