Automated EEG-based language detection using directed quantum pattern technique
Electroencephalogram (EEG) signals contain complex useful information about brain
activities. These EEG signals are noisy, highly varying and nonstationary in nature. Hence …
activities. These EEG signals are noisy, highly varying and nonstationary in nature. Hence …
Fully end-to-end EEG to speech translation using multi-scale optimized dual generative adversarial network with cycle-consistency loss
C Ma, Y Zhang, Y Guo, X Liu, H Shangguan, J Wang… - Neurocomputing, 2025 - Elsevier
Decoding auditory evoked electroencephalographic (EEG) signals to correlate them with
speech acoustic features and construct transitional signals between different domain signals …
speech acoustic features and construct transitional signals between different domain signals …
[PDF][PDF] Deep Neural Ensemble Classification for COVID-19 Dataset
MAFBW Hamzah, A Sambas, YAB El-Ebiary - pdfs.semanticscholar.org
The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has profoundly
impacted global health, economies, and daily life [1]. Since its emergence in late 2019 …
impacted global health, economies, and daily life [1]. Since its emergence in late 2019 …
[PDF][PDF] EXPLORING THE IMPACT OF CRYPTOCURRENCIES ON SHAPING GLOBAL TRADE AND ECONOMIC DYNAMICS: TRANSITIONING FROM TRADITIONAL …
SS AFFANDI - academia.edu
This study explores the potential of cryptocurrencies to reshape global commerce and
economic interactions. It traces the evolution from traditional fiat currencies to the …
economic interactions. It traces the evolution from traditional fiat currencies to the …
[PDF][PDF] Enhancement Of Finger State Progress Model for Markerless Virtual Fine Motor Stroke Rehabilitation
The use of machine learning as a tool for analyzing and pattern extraction from the results is
widely applied in various medical applications in stroke rehabilitation. It will help the …
widely applied in various medical applications in stroke rehabilitation. It will help the …