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ÇѱÛÁ¦¸ñ(Korean Title) |
Drowsiness Classification using Convolutional Neural Network based on Electroencephalography Signals |
¿µ¹®Á¦¸ñ(English Title) |
Drowsiness Classification using Convolutional Neural Network based on Electroencephalography Signals |
ÀúÀÚ(Author) |
Seong-Hyun Yu
Hyeong-Yeong Park
Euijong Lee
Ji-Hoon Jeong
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¿ø¹®¼ö·Ïó(Citation) |
VOL 29 NO. 02 PP. 0680 ~ 0680 (2022. 11) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
¤ý Goals
- Binary classification of drowsiness states and alert states using electroencephalogram(EEG) signals
¤ý Motivation
- Detection drowsiness in diving environments was mostly achieved through visual technology-based cameras [1]
- The mental state of the general public can be detected based on neurophysiological signals
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Å°¿öµå(Keyword) |
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ÆÄÀÏ÷ºÎ |
PDF ´Ù¿î·Îµå
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