Search Results - "Two-phase Multitask Autoencoder"

TWEN: EEG Emotion Recognition Model Based on Weakly Supervised Learning Framework with Two-Phase Multitask Autoencoder

Authors: Taewan Kim ChangGyun Jin Seong-Eun Kim

Source: 2024 15th International Conference on Information and Communication Technology Convergence (ICTC). :1494-1498

Two-Phase Multitask Autoencoder-Based Deep Learning Framework for Subject-Independent EEG Motor Imagery Classification

Authors: Changgyun Jin Andrew H. Song Seong-Eun Kim

Source: IEEE Access, Vol 12, Pp 77356-77367 (2024)

Subject Terms: subject-independent, 0301 basic medicine, 0303 health sciences, 03 medical and health sciences, motor imagery, deep learning, EEG, Electrical engineering. Electronics. Nuclear engineering, multitask autoencoder, Classification, TK1-9971

Access URL: https://doaj.org/article/e224854d86d643978058e2430c63f522

Data from Seoul National University of Science and Technology Update Knowledge in Engineering (Two-Phase Multitask Autoencoder-Based Deep Learning Framework for Subject-Independent EEG Motor Imagery Classification).

Source: Health & Medicine Week. 6/21/2024, p1251-1251. 1p.

A combination of deep learning models and type-2 fuzzy for EEG motor imagery classification through spatiotemporal-frequency features.

Authors: Jiang, Ensong Huang, Tangsen Yin, Xiangdong

Source: Journal of Medical Engineering & Technology; Oct2024, Vol. 48 Issue 7, p262-275, 14p

Subject Terms: BIOMEDICAL signal processing, ARTIFICIAL intelligence, MOTOR imagery (Cognition), OPTIMIZATION algorithms, DATABASES, DEEP learning