Consumer Personalized Gesture Recognition in UAV-Based Industry 5.0 Applications
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F23%3A43907916" target="_blank" >RIV/60076658:12310/23:43907916 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10229211" target="_blank" >https://ieeexplore.ieee.org/document/10229211</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TCE.2023.3308209" target="_blank" >10.1109/TCE.2023.3308209</a>
Alternative languages
Result language
angličtina
Original language name
Consumer Personalized Gesture Recognition in UAV-Based Industry 5.0 Applications
Original language description
In the era of Industry 5.0, technology promises the rapid and smart growth of industries to improve the system performance substantially and be sustainable and more secure. Industry 5.0 enabled the conventional unmanned aerial vehicle (UAV) industries to represent a dynamic result that can offer various services irrespective of time, place, and in broader physical range. Hence, satellite systems of high performance having advanced pre-processing transmission capabilities are gaining considerable attention to increase overall system throughput. In enhancing the efficiency of interaction between humans and machines, gesture recognition in UAV-based industry 5.0 can perform a vital role as the transmission medium in end-user based applications with low latency periods. However, few smart consumer personalized gesture recognition (CPGR) systems are insufficient in the privacy preservation in UAV-based industry 5.0 applications. Also, privacy-preserving is time-consuming, especially for model training and real-time CPGR. Although wireless technologies with big-data schemes provide such applications but lack emotional attachments. This article proposes a gesture-aware system with pre-processing connected systems using a powerful emotion detection system by incorporating a conventional analysis-modification-synthesis framework used for industry 5.0 applications. This study demonstrates the effectiveness of different noise estimation techniques on the proposed Modulation domain Recognition (MDSR) approach for UAV-based Industry 5.0.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS
ISSN
0098-3063
e-ISSN
1558-4127
Volume of the periodical
69
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
8
Pages from-to
842-849
UT code for WoS article
001164696000005
EID of the result in the Scopus database
2-s2.0-85168699275