Theoretical Model and Implementation Path of Party Building Intelligent Networks in Colleges and Universities from the Perspective of Artificial Intelligence

The paper aims to promote the growth of party building work in colleges and universities to improve school party organization, team management and strengthen party member ideological construction and overall party quality. We design intelligent party member business knowledge learning classrooms usi...

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Bibliographic Details
Published inMobile information systems Vol. 2022; pp. 1 - 11
Main Authors Wang, Jiwei, Dang, Man
Format Journal Article
LanguageEnglish
Published Amsterdam Hindawi 16.05.2022
Hindawi Limited
Subjects
Algorithms
Artificial intelligence
Artificial neural networks
Bias
Classrooms
Colleges & universities
Consciousness
Deep learning
Discriminant analysis
Education
Educational technology
Face recognition
Intelligent networks
Machine learning
Neural networks
Students
Teaching
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Summary:The paper aims to promote the growth of party building work in colleges and universities to improve school party organization, team management and strengthen party member ideological construction and overall party quality. We design intelligent party member business knowledge learning classrooms using deep learning to improve the quality of party members. First, we develop a convolutional neural network (CNN)-based classroom face recognition system and improve its loss function using the associated theory of the Visual Geometry Group 16 (VGG-16) model. Then, using the Single Shot Multi-Box Detector (SSD), we establish a classroom standing behavior identification system. The experimental results demonstrate that the accuracy rate of the conventional VGG-16 in the face recognition system is 93.5%, while the upgraded VGG-16 is 96.5%, with a 3.2% increase over the baseline models.
ISSN:1574-017X
1875-905X
DOI:10.1155/2022/3926970