卷积神经网络模型发展及应用

打开文本图片集

关键词：卷积神经网络；图像识别；语义分割；自然语言处理

doi：10.3969/J.ISSN.1672-7274.2025.04.037

中图分类号：TP183 文献标志码：A 文章编码：1672-7274（2025）04-0108-03

Abstract： With the rapid development of information technology，the scale and complexity of dataare constantly increasing.In this context， traditional machine learning algorithms face many chalenges when dealing with largescale data and complex tasks. Convolutional neural network models，as a deep learning algorithm，have emerged and rapidly developed.The article elaborates on the roles of the input layer，hidden layer，and output layer in the structure of convolutional neural network models.The article also reviews the development processof convolutional neural network models， which have gone through multiple stages，and introduces their practical appications in image recognition，semanticsgmentation，objecttracking，naturallanguage processing，intelligentrecommendationsstems， security monitoring，and agriculture.Convolutional neural network models playan importantrolein multiple felds due to their advantages，providing strong support for the intellgent development of various industries and having broad prospects for future development.

Keywords： convolutional neural network; image recognition; semanticsegmentation; natural language processing

当前在人工智能领域，卷积神经网络模型的发展可谓突飞猛进。（剩余4428字）