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

Author:

Wang Jiwei1ORCID,Dang Man2

Affiliation:

1. College of Marxism, Zhengzhou University of Light Industry, Zhengzhou, Henan 450000, China

2. East Campus, Henan University of Economics and Law, Zhengzhou, Henan 450046, China

Abstract

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.

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Computer Science Applications

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