Deep Learning Based Continuous Real-Time Driver Fatigue Detection for Embedded System

Civik, Esra; Yüzgeç, Uğur

doi:10.1109/siu49456.2020.9302035

Cited by 4 publications

(1 citation statement)

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“…Göz ve ağız tespiti için yapılan diğer bir çalışmada göz algılama için 674 görüntü ve ağız algılama modeli için 623 görüntü kullanmıştır. Sistemin doğruluğu %90 üzeri olduğu görülmüştür [10]. Yolo tabanlı bir çalışmada yüz tespiti yapılmış yüz algılama sistemleri için bir iyileştirme önermek için VGG16 modeli kullanılmıştır hassasiyet %95 olarak ölçülmüştür [11].…”

Section: Introductionunclassified

Facial Limb Detection for the Protection of Face in Occupational Safety

Adak

Necmettin

2022

acperpro

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A little carelessness may endanger life safety or loss of life may occur in heavy industry, factories and sectors where occupational safety is very important. In order to prevent or minimize them, it is necessary to take advantage of informatics facilities. Today, the fact that artificial intelligence and the internet of things have come to a very advanced position can provide life safety by developing autonomous systems and building modules that will give warnings, warning the employee working in these sectors in a wrong position immediately. In this study, a YOLO-based system was developed and a proposal was made that aims to protect human facial parts. Tests show that results can be obtained quickly and to prevent harm to life.

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Section: Introductionunclassified