Detection of Driver Distraction using YOLOv5 Network
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The impact of deaths and injuries on families and society is increasing the willingness of the authorities to investigate the cause of the increasing traffic accidents day by day. It is important to emphasize that the majority of traffic accidents are attributed to driver distraction. The role of mobile phones and cigarette usage on driver distraction is a well-known fact. In this study, the authors focus on detecting mobile phone usage and smoking in-vehicle environment. The images collected with a mobile phone docked on the windshield and a yolov5s network is trained with manually labeled images. As a consequence of the study, the authors achieved to distinguish drivers and passengers. Also, they investigate to improve detecting other labeled classes such as 'DriverHand', 'PassengerHand', 'DriverHandWithPhone', etc. © 2021 IEEE.
Açıklama
2nd Global Conference for Advancement in Technology, GCAT 2021 -- 1 October 2021 through 3 October 2021 -- Bangalore -- 173912
Anahtar Kelimeler
cell phone detection; cigarette usage detection; Driver distraction; Yolov5
Kaynak
2021 2nd Global Conference for Advancement in Technology, GCAT 2021
WoS Q Değeri
Scopus Q Değeri
N/A
