Adoption of Deep Learning and recognition of emotion across E-learning platforms with implementation of Blockchain across various devices
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F25%3A39923676" target="_blank" >RIV/00216275:25410/25:39923676 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1016/j.procs.2025.07.012" target="_blank" >https://doi.org/10.1016/j.procs.2025.07.012</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.procs.2025.07.012" target="_blank" >10.1016/j.procs.2025.07.012</a>
Alternative languages
Result language
angličtina
Original language name
Adoption of Deep Learning and recognition of emotion across E-learning platforms with implementation of Blockchain across various devices
Original language description
The drastic improvement in E-learning platform has transformed online education by providing unmatched flexibility and accessibility. However, the absence of face-to-face interaction has been challenging in keeping students under observation and elevating their engagement across E-learning platforms. This research paper proposes to combine Deep Learning (DL) and recognition of emotion in E-learning platforms with implementation of Blockchain technology across various devices, to manage challenges associated with observation and engagement of students in e-platforms. By reviewing the emotional state of a student using facial expressions, the proposed system would emphases on enhanced personalized learning experience by utilizing Blockchain Technology to ensure data security. This research paper is an attempt to explain the combination of Deep Learning and Blockchain thereby improving the effectiveness of E-learning platforms.
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
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
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Procedia Computer Science: International Conference on Industry Sciences and Computer Science Innovation (iSCSi’24)
ISBN
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ISSN
1877-0509
e-ISSN
1877-0509
Number of pages
8
Pages from-to
90-97
Publisher name
Elsevier B.V.
Place of publication
Amsterdam
Event location
Porto
Event date
Oct 29, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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