摘要
深度学习为全自动人工智能慕课生成系统提供理论支撑,其中卷积神经网络(Convolutional Neural Network,CNN)、循环神经网络(Recurrent Neural Network,RNN)及其变体发挥重要作用。该系统通过课程内容自动生成、视频智能剪辑、交互界面自动构建等模块协同运作。利用自然语言处理、计算机视觉技术实现关键功能,借助分布式存储、图形处理器(Graphics Processing Unit,GPU)集群等优化数据处理与系统性能,旨在构建高效、智能的慕课生成体系。
Deep learning provides theoretical support for fully automated artificial intelligence MOOC generation systems,in which convolutional neural networks(CNN),recurrent neural networks(RNN),and their variants play important roles.The system operates collaboratively through modules such as automatic generation of course content,intelligent video editing,and automatic construction of interactive interfaces.Utilizing natural language processing and computer vision technology to achieve key functions,optimizing data processing and system performance through distributed storage,graphics processing unit(GPU)clusters,etc.,aiming to build an efficient and intelligent MOOC generation system.
作者
李可昕
LI Kexin(Jiangxi Tellhow Animation College,Nanchang Jiangxi 330200,China)
出处
《信息与电脑》
2025年第13期107-109,共3页
Information & Computer
关键词
深度学习
慕课生成系统
自然语言处理
计算机视觉
分布式存储
deep learning
MOOC generation system
natural language processing
computer vision
distributed storage
作者简介
李可昕,女,硕士,助教。研究方向:人工智能。
