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Byeong-Hoo Lee

14 papers hereh-index 8286 citations22 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author8
  • middle author4
  • last author1

Across the 13 of 14 papers where every author was matched, so the position is known.

fields
  • cs.HC8
  • eess.SP3
  • cs.AI1
  • cs.CV1
  • cs.LG1

identity via Semantic Scholar / OpenAlex

activity
20202024
collaborators
Showing 2020Show all

4 papers · 1 filter

cs.HC2020

Speech Imagery Classification using Length-Wise Training based on Deep Learning

Byeong-Hoo Lee, Byeong-Hee Kwon, Do-Yeun Lee +1

Brain-computer interface uses brain signals to control external devices without actual control behavior. Recently, speech imagery has been studied for direct communication using la…

cs.HC2020

Motor Imagery Classification Emphasizing Corresponding Frequency Domain Method based on Deep Learning Framework

Byoung-Hee Kwon, Byeong-Hoo Lee, Ji-Hoon Jeong

The electroencephalogram, a type of non-invasive-based brain signal that has a user intention-related feature provides an efficient bidirectional pathway between user and computer.…

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…

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…

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