Gender recognition using thermal images from UAV
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F21%3A39917500" target="_blank" >RIV/00216275:25410/21:39917500 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9497627" target="_blank" >https://ieeexplore.ieee.org/document/9497627</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IDT52577.2021.9497627" target="_blank" >10.1109/IDT52577.2021.9497627</a>
Alternative languages
Result language
angličtina
Original language name
Gender recognition using thermal images from UAV
Original language description
Gender recognition is one of the issues that computer vision deals with. It is useful for analysing human behaviour, intelligent tracking, or human-robot interaction. The aim of this paper is to recognise the gender of people in outdoor areas, where it is very difficult or impossible to guard all access roads to the place, even in poor lighting conditions or in the dark. In this paper, a model will be designed and tested using a controlled UAV flight, during which images of people were obtained. The sensor is a thermal camera located on the UA V , which is not dependent on ambient lighting, and deep learning methods are used for subsequent image processing and classification. These are convolutional neural networks (AlexNet, GoogLeNet), which will be used to solve binary classification. Optimized networks achieve classification accuracy of 81.6 %% (GoogLeNet) and 82.3% (AlexNet). A freely available database [21] was used to learn CNNs, and a self-created database (images obtained with a thermal camera attached to a UAV) was used to test the networks.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of The International Conference on Information and Digital Technologies 2021
ISBN
978-1-66543-692-2
ISSN
2575-677X
e-ISSN
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Number of pages
6
Pages from-to
83-88
Publisher name
IEEE (Institute of Electrical and Electronics Engineers)
Place of publication
New York
Event location
Žilina
Event date
Jun 22, 2021
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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