A Study of Deep CNN-Based Classification of Open and Closed Eyes Using a Visible Light Camera Sensor.

Kim, Ki Wan; Hong, Hyung Gil; Nam, Gi Pyo; Park, Kang Ryoung.

Afiliação

Kim KW; Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea. yawara18@dgu.edu.
Hong HG; Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea. hell@dongguk.edu.
Nam GP; Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea. oscar1201@dgu.edu.
Park KR; Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea. parkgr@dongguk.edu.

Sensors (Basel) ; 17(7)2017 Jun 30.

Article em En | MEDLINE | ID: mdl-28665361

Palavras-chave

classification of open and closed eyes; deep residual convolutional neural network; eye status tracking-based driver drowsiness detection; visible light camera

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article