Classification of different types of DDR RAM using transfer learning in convolutional learning networks

Q4 Engineering
{"title":"Classification of different types of DDR RAM using transfer learning in convolutional learning networks","authors":"","doi":"10.59018/022434","DOIUrl":null,"url":null,"abstract":"Technology, specifically computers play an important role in modern society. People who are new to computers can determine what type of RAM they have, which can be used to avoid confusion on what type of RAM their computer needs with the help of an Android device. For this study, a powerful computer with a Graphics Processing Unit (GPU) needed to be used to shorten the amount of time that the deep learning process takes. The study gathered images of 4 types of Random Access Memory for a RAM classification system. There were 1000 images in total for DDR1, DDR2, DDR3, and DDR4 RAM. The study utilized transfer learning to RAM type classification with pre-trained models such as VGG16, VGG19, Inception V3, and Xception. The data that was gathered showed that Xception is the best classifier with an initial average accuracy of 85.034% and a 100% Val_Accuracy even though the model had the longest loading time with 12 seconds.","PeriodicalId":38652,"journal":{"name":"ARPN Journal of Engineering and Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ARPN Journal of Engineering and Applied Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59018/022434","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0

Abstract

Technology, specifically computers play an important role in modern society. People who are new to computers can determine what type of RAM they have, which can be used to avoid confusion on what type of RAM their computer needs with the help of an Android device. For this study, a powerful computer with a Graphics Processing Unit (GPU) needed to be used to shorten the amount of time that the deep learning process takes. The study gathered images of 4 types of Random Access Memory for a RAM classification system. There were 1000 images in total for DDR1, DDR2, DDR3, and DDR4 RAM. The study utilized transfer learning to RAM type classification with pre-trained models such as VGG16, VGG19, Inception V3, and Xception. The data that was gathered showed that Xception is the best classifier with an initial average accuracy of 85.034% and a 100% Val_Accuracy even though the model had the longest loading time with 12 seconds.
利用卷积学习网络中的迁移学习对不同类型的 DDR RAM 进行分类
技术,特别是计算机在现代社会中发挥着重要作用。初学电脑的人可以通过安卓设备来确定自己的内存类型,从而避免混淆电脑所需的内存类型。在这项研究中,需要使用带有图形处理器(GPU)的强大计算机,以缩短深度学习过程所需的时间。这项研究收集了 4 种随机存取存储器的图像,用于 RAM 分类系统。DDR1、DDR2、DDR3 和 DDR4 内存共有 1000 张图像。研究利用迁移学习对 RAM 类型进行分类,并使用了 VGG16、VGG19、Inception V3 和 Xception 等预训练模型。收集到的数据显示,Xception 是最好的分类器,初始平均准确率为 85.034%,Val_Accuracy 为 100%,尽管该模型的加载时间最长,需要 12 秒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
ARPN Journal of Engineering and Applied Sciences
ARPN Journal of Engineering and Applied Sciences Engineering-Engineering (all)
CiteScore
0.70
自引率
0.00%
发文量
7
期刊介绍: ARPN Journal of Engineering and Applied Sciences (ISSN 1819-6608) is an online peer-reviewed International research journal aiming at promoting and publishing original high quality research in all disciplines of engineering sciences and technology. All research articles submitted to ARPN-JEAS should be original in nature, never previously published in any journal or presented in a conference or undergoing such process across the globe. All the submissions will be peer-reviewed by the panel of experts associated with particular field. Submitted papers should meet the internationally accepted criteria and manuscripts should follow the style of the journal for the purpose of both reviewing and editing. Our mission is -In cooperation with our business partners, lower the world-wide cost of research publishing operations. -Provide an infrastructure that enriches the capacity for research facilitation and communication, among researchers, college and university teachers, students and other related stakeholders. -Reshape the means for dissemination and management of information and knowledge in ways that enhance opportunities for research and learning and improve access to scholarly resources. -Expand access to research publishing to the public. -Ensure high-quality, effective and efficient production and support good research and development activities that meet or exceed the expectations of research community. Scope of Journal of Engineering and Applied Sciences: -Engineering Mechanics -Construction Materials -Surveying -Fluid Mechanics & Hydraulics -Modeling & Simulations -Thermodynamics -Manufacturing Technologies -Refrigeration & Air-conditioning -Metallurgy -Automatic Control Systems -Electronic Communication Systems -Agricultural Machinery & Equipment -Mining & Minerals -Mechatronics -Applied Sciences -Public Health Engineering -Chemical Engineering -Hydrology -Tube Wells & Pumps -Structures
文献相关原料
公司名称 产品信息 采购帮参考价格
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信