Lie detection using extreme learning machine: A concealed information test based on short‐time Fourier transform and binary bat optimization using a novel fitness function

Lie detection is one of the major challenges that is being faced by the forensic sciences. Identification of lie on the basis of a person's mental behavior is a tedious task. Brain‐computer interface is one such medium which provides a solution to this problem by displaying visual stimuli and r...

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Veröffentlicht in:	Computational intelligence Jg. 36; H. 2; S. 637 - 658
Hauptverfasser:	Dodia, Shubham, Edla, Damodar R., Bablani, Annushree, Cheruku, Ramalingaswamy
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken, USA John Wiley & Sons, Inc 01.05.2020 Blackwell Publishing Ltd
Schlagworte:	Algorithms Artificial neural networks binary bat Brain brain‐computer interface concealed information test electroencephalogram extreme learning machine Feature extraction Forensic science Fourier transforms Machine learning Optimization short‐time Fourier transform Visual stimuli
ISSN:	0824-7935, 1467-8640
Online-Zugang:	Volltext
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