Mental workload assessment using deep learning models from EEG signals: a systematic review
K Kingphai, Y Moshfeghi - IEEE Transactions on Cognitive and …, 2024 - ieeexplore.ieee.org
Mental workload (MWL) assessment is crucial in information systems (IS), impacting task
performance, user experience, and system effectiveness. Deep learning offers promising …
performance, user experience, and system effectiveness. Deep learning offers promising …
INOVASI BIMBINGAN SPIRITUAL ISLAM MELALUI PENDEKATAN DEEP LEARNING DALAM AL-QUR'AN
B Syafaruddin… - AL-WAJID: JURNAL …, 2024 - ejournal.iain-bone.ac.id
Era digital telah membawa transformasi fundamental dalam berbagai aspek kehidupan
manusia, tidak terkecuali dalam ranah spiritualitas dan keagamaan. Bimbingan spiritual …
manusia, tidak terkecuali dalam ranah spiritualitas dan keagamaan. Bimbingan spiritual …
MeDiANet: A Lightweight Network for Large-scale Multi-disease Classification of Multi-modal Medical Images Using Dilated Convolution and Attention Network
Medical image classification is a critical component of modern healthcare, providing
numerous advantages, including improved diagnostic accuracy and treatment planning …
numerous advantages, including improved diagnostic accuracy and treatment planning …
Deep learning classification model of mental workload levels using EEG signals
K Kingphai - 2024 - stax.strath.ac.uk
Understanding and improving humance performance, especially in situations that require
safety, productivity, and well-being, relies on categorising mental workload (MWL) …
safety, productivity, and well-being, relies on categorising mental workload (MWL) …