Aerial Landscape Recognition via Multi-Input Neural Network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F21%3A00557774" target="_blank" >RIV/60162694:G43__/21:00557774 - isvavai.cz</a>
Alternative codes found
RIV/60162694:G38__/21:00557774 RIV/00216305:26620/21:PU143713
Result on the web
<a href="http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9502737" target="_blank" >http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9502737</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICMT52455.2021.9502749" target="_blank" >10.1109/ICMT52455.2021.9502749</a>
Alternative languages
Result language
angličtina
Original language name
Aerial Landscape Recognition via Multi-Input Neural Network
Original language description
Throughout the last decade, the advancements in the hardware allow use for wider applications of the unmanned aerial vehicles (UAV). UAVs feature significant advantages in autonomous aerial landscape mapping and recognition (ALR) over traditional methods due to their high level of operationality and mission repeatability, along with a simple alteration of e.g., on board remote sensors. ALR system based on convolutional neural networks is proposed. The system is designed with real-time capabilities. Data classification based on histogram and Gabor filter is explored on commercially available aerial images. The research roadmap designed to offload the dependency of the process on flight testing to improve the cost-efficiency of the development is proposed as well.
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
20301 - Mechanical engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
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
2021 8th International Conference on Military Technologies, ICMT 2021 - Proceedings
ISBN
978-1-6654-3724-0
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
1-5
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
Piscataway, USA
Event location
Brno, the Czech Republic
Event date
Jun 8, 2021
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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