检索结果-南通市图书馆

LDNet: A Robust Hybrid Approach for Lie Detection Using Deep Learning Techniques

Computers, Materials & Continua 2024年第11期81卷 2845-2871页

作者： shanjita akter prome Md Rafiqul Islam Md.Kowsar Hossain Sakib David Asirvatham Neethiahnanthan Ari Ragavan Cesar Sanin Edward Szczerbicki School of Computer Science Taylor’s UniversitySubang Jaya47500Malaysia Information Systems Australian Institute of Higher EducationSydneyNSW 2000Australia Faculty of Social Sciences&Leisure Management Taylor’s UniversitySubang Jaya47500Malaysia Faculty of Management and Economics Gdansk University of TechnologyGdansk80-233Poland

Deception detection is regarded as a concern for everyone in their daily lives and affects social *** human face is a rich source of data that offers trustworthy markers of *** deception or lie detection systems are non-intrusive,cost-effective,and mobile by identifying facial *** the last decade,numerous studies have been conducted on deception detection using several advanced *** have focused their attention on inventing more effective and efficient solutions for the detection of ***,it could be challenging to spot trends,practical approaches,gaps,and chances for ***,there are still a lot of opportunities for innovative deception detection ***,we used a variety of machine learning(ML)and deep learning(DL)approaches to experiment with this *** research aims to do the following:(i)review and analyze the current lie detection(LD)systems;(ii)create a dataset;(iii)use several ML and DL techniques to identify lying;and(iv)create a hybrid model known as *** combining layers from Vgg16 and DeneseNet121,LDNet was developed and offered the best accuracy(99.50%)of all the *** developed hybrid model is a great addition that significantly advances the study of *** findings from this research endeavor are expected to advance our understanding of the effectiveness of ML and DL techniques in ***,it has significant practical applications in diverse domains such as security,law enforcement,border control,organizations,and investigation cases where accurate lie detection is paramount.

关键词： Artificial intelligence deception/lie detection deep learning facial expression machine learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：