基于卷积神经网络模型的智能媒资编目技术研究与实践  

Research and Practice of Intelligent Media Asset Cataloguing Technology Based on Convolutional Neural Network

作　　者：宋庆 Song Qing(Shangyu Convergence Media Center,Shaoxing,Zhejiang 312300,China)

机构地区：[1]绍兴市上虞区融媒体中心,浙江312300

出　　处：《广播与电视技术》2024年第5期55-58,共4页Radio & TV Broadcast Engineering

摘　　要：本文基于融媒体中心AI智能媒资系统建设,研究分析卷积神经网络算法在媒资编目时的相关技术应用,并与深度学习、自然语言处理等技术相结合,可以实现更智能、更自动化的媒体资源处理和分析。Based on the construction of an AI intelligent media asset system in the integrated media center,this article studies and analyzes the relevant technical applications of convolutional neural network algorithms in media asset cataloging,and combines them with technologies such as deep learning and natural language processing to achieve more intelligent and automated media asset processing and analysis.

关 键 词：卷积神经网络算法 智能媒资系统 媒体行业 人工智能 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]