most citedGradual Relation Network: Decoding Intuitive Upper Extremity Movement Imaginations Based on Few-Shot EEG Learning

3 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.NE20203 cited

Gradual Relation Network: Decoding Intuitive Upper Extremity Movement Imaginations Based on Few-Shot EEG Learning

Kyung-Hwan Shim, Ji-Hoon Jeong, Seong-Whan Lee

Brain-computer interface (BCI) is a communication tool that connects users and external devices. In a real-time BCI environment, a calibration procedure is particularly necessary f…

cs.HC2020

Motor Imagery Classification of Single-Arm Tasks Using Convolutional Neural Network based on Feature Refining

Byeong-Hoo Lee, Ji-Hoon Jeong, Kyung-Hwan Shim +1

Brain-computer interface (BCI) decodes brain signals to understand user intention and status. Because of its simple and safe data acquisition process, electroencephalogram (EEG) is…

cs.HC2020

Classification of Upper Limb Movements \newline Using Convolutional Neural Network \newline with 3D Inception Block

D. -Y. Lee, J. -H. Jeong, K. -H. Shim +1

A brain-machine interface (BMI) based on electroencephalography (EEG) can overcome the movement deficits for patients and real-world applications for healthy people. Ideally, the B…

eess.SP2020

Classification of High-Dimensional Motor Imagery Tasks based on An End-to-end role assigned convolutional neural network

Byeong-Hoo Lee, Ji-Hoon Jeong, Kyung-Hwan Shim +1

A brain-computer interface (BCI) provides a direct communication pathway between user and external devices. Electroencephalogram (EEG) motor imagery (MI) paradigm is widely used in…

eess.SP2020

Decoding Movement Imagination and Execution from EEG Signals using BCI-Transfer Learning Method based on Relation Network

D. -Y. Lee, J. -H. Jeong, K. -H. Shim +1

A brain-computer interface (BCI) is used not only to control external devices for healthy people but also to rehabilitate motor functions for motor-disabled patients. Decoding move…