Performance Comparison of Deep CNN Models for Detecting Driver’s Distraction
نویسندگان
چکیده
According to various worldwide statistics, most car accidents occur solely due human error. The person driving a needs be alert, especially when travelling through high traffic volumes that permit high-speed transit since slight distraction can cause fatal accident. Even though semiautomated checks, such as speed detecting cameras and barriers, are deployed, controlling errors is an arduous task. key causes of driver’s include drunken driving, conversing with co-passengers, fatigue, operating gadgets while driving. If these distractions accurately predicted, the drivers alerted alarm system. Further, this research develops deep convolutional neural network (deep CNN) models for predicting reason behind distraction. CNN trained using numerous images distracted drivers. performance deepCNNmodels, namely theVGG16,ResNet, Xception network, assessed based on evaluation metrics, precision score, recall/sensitivity F1 specificity score. ResNet model outperformed all other best detection determining drivers’ activities.
منابع مشابه
Fine-tuning deep CNN models on specific MS COCO categories
Fine-tuning of a deep convolutional neural network (CNN) is oen desired. is paper provides an overview of our publicly available py-faster-rcnn- soware library that can be used to ne-tune the VGG CNN M 1024 model on custom subsets of the Microso Common Objects in Context (MS COCO) dataset. For example, we improved the procedure so that the user does not have to look for suitable image le...
متن کاملcomparison of zoe and vitapex for canal treatment of necrotic primary teeth
چکیده ندارد.
15 صفحه اولDetecting distraction and degraded driver performance with visual behavior metrics
Driver distraction contributes to approximately 43% of motor-vehicle crashes and 27% of near-crashes. Rapidly developing in-vehicle technology and electronic devices place additional demands on drivers, which might lead to distraction and diminished capacity to perform driving tasks. This situation threatens safe driving. Technology that can detect and mitigate distraction by alerting drivers c...
متن کاملDetecting driver distraction
The increasing use of in-vehicle information systems (IVISs), such as navigation devices and MP3 players, can jeopardize safety by introducing distraction into driving. One way to address this problem is to develop distraction mitigation systems, which adapt IVIS functions according to driver state. In such a system, correctly identifying driver distraction is critical, which is the focus of th...
متن کاملassessment of the park- ang damage index for performance levels of rc moment resisting frames
چکیده هدف اصلی از طراحی لرزه ای تامین ایمنی جانی در هنگام وقوع زلزله و تعمیر پذیر بودن سازه خسارت دیده، پس از وقوع زلزله است. تجربه زلزله های اخیر نشان داده است که ساختمان های طراحی شده با آیین نامه های مبتنی بر نیرو از نظر محدود نمودن خسارت وارده بر سازه دقت لازم را ندارند. این امر سبب پیدایش نسل جدید آیین نامه های مبتنی بر عملکرد شده است. در این آیین نامه ها بر اساس تغییرشکل های غیرارتجاعی ...
15 صفحه اولذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computers, materials & continua
سال: 2021
ISSN: ['1546-2218', '1546-2226']
DOI: https://doi.org/10.32604/cmc.2021.016736