用激活函数增强CNNHQ

Abdulrahman Kariri, Mohammed Aljamal, Jinan Al Aridhee, Ismaiel Albukhari, Nadine Matondo-Mvula, K. Elleithy
{"title":"用激活函数增强CNNHQ","authors":"Abdulrahman Kariri, Mohammed Aljamal, Jinan Al Aridhee, Ismaiel Albukhari, Nadine Matondo-Mvula, K. Elleithy","doi":"10.1109/LISAT58403.2023.10179557","DOIUrl":null,"url":null,"abstract":"In this paper, we present an overview of quantum neural network (QNN) and quantum computing benefits in the Artificial Intelligence field with methods used to enhance the application of machine learning. The approach uses quantum computers to enhance Convolutional Neural Network (CNN) with Hybrid QNNs using IBM Qiskit called the Convolutional Neural Network Hybrid Qiskit (CNNHQ). This paper will compare and focus on using the quantum concepts of computation to develop and optimize the network process entirely depending on Activation functions used in the neural network approach.","PeriodicalId":250536,"journal":{"name":"2023 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancement of CNNHQ with an Activation Function\",\"authors\":\"Abdulrahman Kariri, Mohammed Aljamal, Jinan Al Aridhee, Ismaiel Albukhari, Nadine Matondo-Mvula, K. Elleithy\",\"doi\":\"10.1109/LISAT58403.2023.10179557\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present an overview of quantum neural network (QNN) and quantum computing benefits in the Artificial Intelligence field with methods used to enhance the application of machine learning. The approach uses quantum computers to enhance Convolutional Neural Network (CNN) with Hybrid QNNs using IBM Qiskit called the Convolutional Neural Network Hybrid Qiskit (CNNHQ). This paper will compare and focus on using the quantum concepts of computation to develop and optimize the network process entirely depending on Activation functions used in the neural network approach.\",\"PeriodicalId\":250536,\"journal\":{\"name\":\"2023 IEEE Long Island Systems, Applications and Technology Conference (LISAT)\",\"volume\":\"84 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE Long Island Systems, Applications and Technology Conference (LISAT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LISAT58403.2023.10179557\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LISAT58403.2023.10179557","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在本文中,我们概述了量子神经网络(QNN)和量子计算在人工智能领域的好处,以及用于增强机器学习应用的方法。该方法使用量子计算机来增强卷积神经网络(CNN)和使用IBM Qiskit的混合qnn,称为卷积神经网络混合Qiskit (CNNHQ)。本文将比较并着重于使用量子计算概念来开发和优化完全依赖于神经网络方法中使用的激活函数的网络过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancement of CNNHQ with an Activation Function
In this paper, we present an overview of quantum neural network (QNN) and quantum computing benefits in the Artificial Intelligence field with methods used to enhance the application of machine learning. The approach uses quantum computers to enhance Convolutional Neural Network (CNN) with Hybrid QNNs using IBM Qiskit called the Convolutional Neural Network Hybrid Qiskit (CNNHQ). This paper will compare and focus on using the quantum concepts of computation to develop and optimize the network process entirely depending on Activation functions used in the neural network approach.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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