Intelligent vehicular networks, deep learning-based sensing technologies, and big data-driven algorithmic decision-making in smart transportation systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F21%3A00002228" target="_blank" >RIV/75081431:_____/21:00002228 - isvavai.cz</a>
Result on the web
<a href="https://www.ceeol.com/search/journal-detail?id=642" target="_blank" >https://www.ceeol.com/search/journal-detail?id=642</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Intelligent vehicular networks, deep learning-based sensing technologies, and big data-driven algorithmic decision-making in smart transportation systems
Original language description
The authors analyze the outcomes of an exploratory review of the current research on intelligent vehicular networks, deep learning-based sensing technologies, and big data-driven algorithmic decision-making in smart transportation systems.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50200 - Economics and Business
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Contemporary Readings in Law and Social Justice
ISSN
1948-9137
e-ISSN
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Volume of the periodical
13
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
14
Pages from-to
107-120
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85120823503