Deep Convolutional Neural Network for Fire Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU136619" target="_blank" >RIV/00216305:26220/20:PU136619 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/RADIOELEKTRONIKA49387.2020.9092344" target="_blank" >http://dx.doi.org/10.1109/RADIOELEKTRONIKA49387.2020.9092344</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/RADIOELEKTRONIKA49387.2020.9092344" target="_blank" >10.1109/RADIOELEKTRONIKA49387.2020.9092344</a>
Alternative languages
Result language
angličtina
Original language name
Deep Convolutional Neural Network for Fire Detection
Original language description
Detection of smoke and fire using deep convolutional neural network to process video signals from camera.
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
20202 - Communication engineering and systems
Result continuities
Project
<a href="/en/project/LO1401" target="_blank" >LO1401: Interdisciplinary Research of Wireless Technologies</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2020 30th International Conference Radioelektronika (Radioelektronika)
ISBN
978-1-7281-6469-4
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1-6
Publisher name
Neuveden
Place of publication
Neuveden
Event location
Bratislava
Event date
Apr 15, 2020
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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