基于大数据分析的海量图像快速分类研究  

Fast Classification of Massive Images Based on Big Data Analysis

作　　者：吕波[1] LV Bo(School of Ya’an Polytechnic College,Ya'an 625000 China)

机构地区：[1]雅安职业技术学院,四川雅安625000

出　　处：《自动化技术与应用》2022年第10期85-88,共4页Techniques of Automation and Applications

基　　金：雅安职业技术学院5G技术应用中心(YZYJG201907)。

摘　　要：为了提高海量图像分类的准确率和图像分类效果,针对当前图像分类精度低,时间长等缺陷,提出了基于大数据分析的海量图像分类方法。首先分析当前图像分类的研究进展,找到不同分类方法存在的不足,然后采集海量图像,对图像进行预处理,并采用大数据分析技术建立图像分类器,通过图像分类器进行图像分类,最后与其它方法进行了图像分类的仿真试验。结果表明:该方法分类图像精度高,分类时间最短,相对其它图像分类方法,具有显著的优越性。In order to improve the accuracy and effect of massive image classification, a massive image classification method based on big data analysis is proposed. Firstly, the research progress of current image classification is analyzed, and the shortcomings of different classification methods are found. Then, a large number of images are collected, the images are preprocessed, the image classifier is established by using big data analysis technology, and the image classifier is used for image classification. Finally, the simulation experiment of image classification is carried out with other methods. The results show that this method has high image classification accuracy and the shortest classification time. It has significant advantages over other image classification methods.

关 键 词：大数据分析 图像分类 卷积神经网络 分类准确率 分类效果 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]