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

作　　者：Shanjita Akter Prome Md Rafiqul Islam Md.Kowsar Hossain Sakib David Asirvatham Neethiahnanthan Ari Ragavan Cesar Sanin Edward Szczerbicki 

机构地区：[1]School of Computer Science,Taylor’s University,Subang Jaya,47500,Malaysia [2]Information Systems,Australian Institute of Higher Education,Sydney,NSW 2000,Australia [3]Faculty of Social Sciences&Leisure Management,Taylor’s University,Subang Jaya,47500,Malaysia [4]Faculty of Management and Economics,Gdansk University of Technology,Gdansk,80-233,Poland

出　　处：《Computers, Materials & Continua》2024年第11期2845-2871,共27页计算机、材料和连续体（英文）

基　　金：funded by the Ministry of Higher Education(MOHE),Malaysia under the Fundamental Research Grant Project(FRGS/1/2021/SS0/TAYLOR/02/6)。

摘　　要：Deception detection is regarded as a concern for everyone in their daily lives and affects social interactions.The human face is a rich source of data that offers trustworthy markers of deception.The deception or lie detection systems are non-intrusive,cost-effective,and mobile by identifying facial expressions.Over the last decade,numerous studies have been conducted on deception detection using several advanced techniques.Researchers have focused their attention on inventing more effective and efficient solutions for the detection of deception.So,it could be challenging to spot trends,practical approaches,gaps,and chances for contribution.However,there are still a lot of opportunities for innovative deception detection methods.Therefore,we used a variety of machine learning(ML)and deep learning(DL)approaches to experiment with this work.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 LDNet.By combining layers from Vgg16 and DeneseNet121,LDNet was developed and offered the best accuracy(99.50%)of all the models.Our developed hybrid model is a great addition that significantly advances the study of LD.The findings from this research endeavor are expected to advance our understanding of the effectiveness of ML and DL techniques in LD.Furthermore,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 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]