EEG-Based Lie Detection Using Autoencoder Deep Learning with Muse II Brain Sensing

AT Hermawan, IAE Zaeni, AP Wibawa… - … Journal of Robotics …, 2024 - pubs2.ascee.org
Detecting deception has significant implications in fields like law enforcement and security.
This research aims to develop an effective lie detection system using …

Concealed Information Test Using Neuro Evolution of Augmenting Topologies

P Raj, DR Edla, SR Parne - Wireless Personal Communications, 2024 - Springer
This research proposal introduces an innovative method for EEG data classification that
leverages Genetic Algorithms and Neural Networks, through the Neuro Evolution of …

EPINET: AN OPTIMIZED, RESOURCE EFFICIENT DEEP GRU-LSTM NETWORK FOR EPILEPTIC SEIZURE PREDICTION

D Kalita, S Dash, KB Mirza - Biomedical Engineering: Applications …, 2024 - World Scientific
The utilization of Electroencephalogram (EEG) as a non-invasive tool to investigate
neurological disorders, particularly epilepsy, by capturing pathological biosignal markers …

TuringEQ: Doğrusal Olmayan Problemler Özelinde Yeni bir Yapay Zekâ Mimarisi

HE Okutan, M Baykara - Fırat Üniversitesi Fen Bilimleri Dergisi, 2024 - dergipark.org.tr
ÖYapay Zekâ alanındaki gelişmelerle birlikte birçok alanda Yapay Zekâ kullanımı
yaygınlaşmış ve bu teknolo**in kullanımı ile önemli başarımlar elde edilmiştir. Elde edilen …

Rozpoznávání skrytých informací k určení intencionální lži pomocí elektroencefalografie

M Žabčíková - 2016 - digilib.k.utb.cz
Rozpoznávání skrytých informací za účelem odhalení intencionální lži představuje klíčovou
výzvu v oblasti bezpečnosti. Současné detektory lži jsou nákladné, nepohodlné a náchylné …