AIMC Topic: Lie Detection

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Multimodal machine learning for deception detection using behavioral and physiological data.

Scientific reports Mar 15, 2025
Deception detection is crucial in domains like national security, privacy, judiciary, and courtroom trials. Differentiating truth from lies is inherently challenging due to many complex, diversified behavioural, physiological and cognitive aspects. T...
Electrocardiography Lie Detection Humans Male Machine Learning India Female Adult Electrooculography Galvanic Skin Response Deception Electroencephalography
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Experimental economics for machine learning-a methodological contribution on lie detection.

PloS one Dec 31, 2024
In this paper, we investigate how technology has contributed to experimental economics in the past and illustrate how experimental economics can contribute to technological progress in the future. We argue that with machine learning (ML), a new techn...
Female Machine Learning Deception Male Humans Lie Detection Economics Algorithms
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An Automatic Lie Detection Model Using EEG Signals Based on the Combination of Type 2 Fuzzy Sets and Deep Graph Convolutional Networks.

Sensors (Basel, Switzerland) Jun 3, 2024
In recent decades, many different governmental and nongovernmental organizations have used lie detection for various purposes, including ensuring the honesty of criminal confessions. As a result, this diagnosis is evaluated with a polygraph machine. ...
Algorithms Female Humans Neural Networks, Computer Male Fuzzy Logic Young Adult Adult Electroencephalography Lie Detection Signal Processing, Computer-Assisted
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Detecting deception with artificial intelligence: promises and perils.

Trends in cognitive sciences Apr 21, 2024
Rapid advancements in artificial intelligence (AI) have driven interest in its potential application for lie detection. Unfortunately, the current approaches have primarily focused on technical aspects at the expense of a solid methodological and the...
Humans Artificial Intelligence Lie Detection Deception
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Machine learning based approach to exam cheating detection.

PloS one Aug 4, 2021
The COVID-19 pandemic has impelled the majority of schools and universities around the world to switch to remote teaching. One of the greatest challenges in online education is preserving the academic integrity of student assessments. The lack of dir...
SARS-CoV-2 Humans Fraud Educational Measurement COVID-19 Models, Theoretical Datasets as Topic Machine Learning Algorithms Universities Education, Distance Lie Detection Deception Pandemics
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Steganographer detection via a similarity accumulation graph convolutional network.

Neural networks : the official journal of the International Neural Network Society Jan 4, 2021
Steganographer detection aims to identify guilty users who conceal secret information in a number of images for the purpose of covert communication in social networks. Existing steganographer detection methods focus on designing discriminative featur...
Lie Detection Social Network Analysis Image Processing, Computer-Assisted Humans Neural Networks, Computer Reproducibility of Results
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Improved semi-supervised autoencoder for deception detection.

PloS one Oct 8, 2019
Existing algorithms of speech-based deception detection are severely restricted by the lack of sufficient number of labelled data. However, a large amount of easily available unlabelled data has not been utilized in reality. To solve this problem, th...
Artificial Intelligence Algorithms Lie Detection Humans Deception
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