Smart Classroom Monitoring Using Novel Real-Time Facial Expression Recognition System
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10250906" target="_blank" >RIV/61989100:27240/22:10250906 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2076-3417/12/23/12134" target="_blank" >https://www.mdpi.com/2076-3417/12/23/12134</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/app122312134" target="_blank" >10.3390/app122312134</a>
Alternative languages
Result language
angličtina
Original language name
Smart Classroom Monitoring Using Novel Real-Time Facial Expression Recognition System
Original language description
Featured Application: The proposed automatic emotion recognition system has been deployed in the classroom environment (education) but it can be used anywhere to monitor the emotions of humans, i.e., health, banking, industries, social welfare etc. Emotions play a vital role in education. Technological advancement in computer vision using deep learning models has improved automatic emotion recognition. In this study, a real-time automatic emotion recognition system is developed incorporating novel salient facial features for classroom assessment using a deep learning model. The proposed novel facial features for each emotion are initially detected using HOG for face recognition, and automatic emotion recognition is then performed by training a convolutional neural network (CNN) that takes real-time input from a camera deployed in the classroom. The proposed emotion recognition system will analyze the facial expressions of each student during learning. The selected emotional states are happiness, sadness, and fear along with the cognitive-emotional states of satisfaction, dissatisfaction, and concentration. The selected emotional states are tested against selected variables gender, department, lecture time, seating positions, and the difficulty of a subject. The proposed system contributes to improve classroom learning.
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
20201 - Electrical and electronic engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Applied Sciences
ISSN
2076-3417
e-ISSN
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Volume of the periodical
12
Issue of the periodical within the volume
23
Country of publishing house
CH - SWITZERLAND
Number of pages
18
Pages from-to
1-18
UT code for WoS article
000895151600001
EID of the result in the Scopus database
2-s2.0-85143724769