Přístupnostní navigace
E-přihláška
Vyhledávání Vyhledat Zavřít
Detail publikace
ZHOU, J. HERENCSÁR, N.
Originální název
Abnormal Behavior Determination Model of Multimedia Classroom Students Based on Multi-task Deep Learning
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
The abnormal behavior of students in the multimedia classroom is not significant, which leads to the difficulty in determining abnormal behavior. Therefore, the abnormal behavior determination model of multimedia classroom students based on multi-task deep learning is constructed. The eigenimage filtering algorithm is used to denoise the captured multimedia classroom student images. The multimedia classroom student images are denoised using an adaptive histogram equalization algorithm to enhance the denoised multimedia classroom student images. The multimedia classroom student images are segmented using the Renyi entropy method, and the student behavioral characteristics are determined based on the image segmentation results. Student behavioral characteristics are determined based on image segmentation results. A multi-task deep learning model is built based on convolutional neural networks. The model mainly uses convolutional neural networks and students' behavioral features to classify students' abnormal behaviors in multimedia classrooms, achieve the determination of abnormal behaviors of multimedia classroom students, and obtain relevant determination results. The experimental results show that the model can effectively determine the abnormal behaviors of students in multimedia classrooms, such as looking to the right and looking left, playing with mobile phones, etc. The accuracy of the determination of abnormal behavior is higher than 98%, and the practical application is good.
Klíčová slova
Multi-task Deep Learning; Multimedia Classroom; Aberrant Student Behavior; Determination Model; Adaptive Histogram Equilibrium; Renyi Entropy
Autoři
ZHOU, J.; HERENCSÁR, N.
Vydáno
19. 8. 2023
Nakladatel
SPRINGER
Místo
NEW YORK
ISSN
1383-469X
Periodikum
MOBILE NETWORKS & APPLICATIONS
Ročník
neuvedeno
Číslo
Stát
Nizozemsko
Strany počet
14
URL
https://link.springer.com/article/10.1007/s11036-023-02187-7
BibTex
@article{BUT184542, author="Jing {Zhou} and Norbert {Herencsár}", title="Abnormal Behavior Determination Model of Multimedia Classroom Students Based on Multi-task Deep Learning", journal="MOBILE NETWORKS & APPLICATIONS", year="2023", volume="neuvedeno", number="neuvedeno", pages="14", doi="10.1007/s11036-023-02187-7", issn="1383-469X", url="https://link.springer.com/article/10.1007/s11036-023-02187-7" }