人工智能在为人们提供隐私方面的作用:调查

Salar Raees, Mohammed Al-Tamimi
{"title":"人工智能在为人们提供隐私方面的作用:调查","authors":"Salar Raees, Mohammed Al-Tamimi","doi":"10.37385/jaets.v5i2.4013","DOIUrl":null,"url":null,"abstract":"Images privacy involves assessing the amount of information leakage from images, assessing risks associated with identification, and examining controls on this information. It was discussed various types of protection available and most commonly used in providing privacy to a person in images, including single-stage and two-stage detection algorithms. The results of each algorithm are organized in detailed tables, and the [YOLO] algorithm expands on all versions. The paper also clarifies the dataset used for testing the algorithms and its relevance to achieving desired results. It presents a comprehensive understanding of the process of detecting persons in digital images and assesses various tools and algorithms for recognizing persons, faces, and identities. It added an extensive examination of the several methods used to identify persons in digital images, with a specific emphasis on safeguarding their privacy. The task at hand is assessing various face recognition and identification tools and algorithms, with a specific emphasis on those that exhibit superior accuracy and efficiency in presenting outcomes. The study concluded that using the yolov8 algorithm in conjunction with blurring techniques effectively conceals individuals' information in digital images while maintaining the integrity of the overall image. The research paper's implications and information can practically contribute to the development of algorithms for detecting and protecting people in digital images, as well as the development of applications in this field. Theoretically, it can enhance understanding of the process of detecting and protecting people, and potentially contribute to the development of new theories in the field of protection and discovery.","PeriodicalId":509378,"journal":{"name":"Journal of Applied Engineering and Technological Science (JAETS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Role of Artificial Intelligence in Providing People With Privacy: Survey\",\"authors\":\"Salar Raees, Mohammed Al-Tamimi\",\"doi\":\"10.37385/jaets.v5i2.4013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Images privacy involves assessing the amount of information leakage from images, assessing risks associated with identification, and examining controls on this information. It was discussed various types of protection available and most commonly used in providing privacy to a person in images, including single-stage and two-stage detection algorithms. The results of each algorithm are organized in detailed tables, and the [YOLO] algorithm expands on all versions. The paper also clarifies the dataset used for testing the algorithms and its relevance to achieving desired results. It presents a comprehensive understanding of the process of detecting persons in digital images and assesses various tools and algorithms for recognizing persons, faces, and identities. It added an extensive examination of the several methods used to identify persons in digital images, with a specific emphasis on safeguarding their privacy. The task at hand is assessing various face recognition and identification tools and algorithms, with a specific emphasis on those that exhibit superior accuracy and efficiency in presenting outcomes. The study concluded that using the yolov8 algorithm in conjunction with blurring techniques effectively conceals individuals' information in digital images while maintaining the integrity of the overall image. The research paper's implications and information can practically contribute to the development of algorithms for detecting and protecting people in digital images, as well as the development of applications in this field. Theoretically, it can enhance understanding of the process of detecting and protecting people, and potentially contribute to the development of new theories in the field of protection and discovery.\",\"PeriodicalId\":509378,\"journal\":{\"name\":\"Journal of Applied Engineering and Technological Science (JAETS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Engineering and Technological Science (JAETS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37385/jaets.v5i2.4013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Engineering and Technological Science (JAETS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37385/jaets.v5i2.4013","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

图像隐私涉及评估从图像中泄露的信息量、评估与识别相关的风险以及检查对这些信息的控制。会议讨论了在为图像中的个人提供隐私保护时可用和最常用的各类保护措施,包括单阶段和双阶段检测算法。每种算法的结果都整理在详细的表格中,[YOLO] 算法对所有版本进行了扩展。论文还阐明了用于测试算法的数据集及其与实现预期结果的相关性。论文全面介绍了在数字图像中检测人员的过程,并评估了用于识别人员、人脸和身份的各种工具和算法。它还对用于识别数字图像中的人员的几种方法进行了广泛的研究,并特别强调要保护他们的隐私。当前的任务是评估各种人脸识别和身份识别工具和算法,重点是那些在呈现结果方面表现出卓越准确性和效率的工具和算法。研究得出的结论是,将 yolov8 算法与模糊技术结合使用,既能有效隐藏数字图像中的个人信息,又能保持整体图像的完整性。该研究论文的意义和信息可切实促进数字图像中人员检测和保护算法的开发,以及该领域应用软件的开发。从理论上讲,它可以加深对人物检测和保护过程的理解,并有可能促进保护和发现领域新理论的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Role of Artificial Intelligence in Providing People With Privacy: Survey
Images privacy involves assessing the amount of information leakage from images, assessing risks associated with identification, and examining controls on this information. It was discussed various types of protection available and most commonly used in providing privacy to a person in images, including single-stage and two-stage detection algorithms. The results of each algorithm are organized in detailed tables, and the [YOLO] algorithm expands on all versions. The paper also clarifies the dataset used for testing the algorithms and its relevance to achieving desired results. It presents a comprehensive understanding of the process of detecting persons in digital images and assesses various tools and algorithms for recognizing persons, faces, and identities. It added an extensive examination of the several methods used to identify persons in digital images, with a specific emphasis on safeguarding their privacy. The task at hand is assessing various face recognition and identification tools and algorithms, with a specific emphasis on those that exhibit superior accuracy and efficiency in presenting outcomes. The study concluded that using the yolov8 algorithm in conjunction with blurring techniques effectively conceals individuals' information in digital images while maintaining the integrity of the overall image. The research paper's implications and information can practically contribute to the development of algorithms for detecting and protecting people in digital images, as well as the development of applications in this field. Theoretically, it can enhance understanding of the process of detecting and protecting people, and potentially contribute to the development of new theories in the field of protection and discovery.
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