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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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

  • 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

  • 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