DEEP NEURAL NETWORK FOR AUTONOMOUS UAV NAVIGATION
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F21%3APU148413" target="_blank" >RIV/00216305:26220/21:PU148413 - isvavai.cz</a>
Result on the web
<a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2021_sbornik_2_v3_DOI.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2021_sbornik_2_v3_DOI.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.13164/eeict.2021.17" target="_blank" >10.13164/eeict.2021.17</a>
Alternative languages
Result language
angličtina
Original language name
DEEP NEURAL NETWORK FOR AUTONOMOUS UAV NAVIGATION
Original language description
The project deals with autonomous drone control. A neural network is used to create autonomous control for object recognition. This recognition is performed with a ground station, where the computer evaluates the position of the drone and autonomously controls the flight of the drone through the detection of objects.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
—
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 II OF THE 27TH STUDENT EEICT 2021 selected papers
ISBN
978-80-214-5943-4
ISSN
—
e-ISSN
—
Number of pages
4
Pages from-to
17-20
Publisher name
Brno University of Technology, Faculty of Electrical Engineering and Communication
Place of publication
Brno
Event location
Brno
Event date
Apr 27, 2021
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
—