Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open …
Driver distraction is one of the main causes of fatal traffic accidents. Therefore, the ability to
detect driver inattention is essential in building a safe yet intelligent transportation system …
detect driver inattention is essential in building a safe yet intelligent transportation system …
A survey on driver behavior analysis from in-vehicle cameras
Distracted or drowsy driving is unsafe driving behavior responsible for thousands of crashes
every year. Studying driver behavior has challenges associated with observing drivers in …
every year. Studying driver behavior has challenges associated with observing drivers in …
Driver behavior detection and classification using deep convolutional neural networks
Driver behavior monitoring system as Intelligent Transportation Systems (ITS) have been
widely exploited to reduce the traffic accidents risk. Most previous methods for monitoring …
widely exploited to reduce the traffic accidents risk. Most previous methods for monitoring …
Driver distraction identification with an ensemble of convolutional neural networks
The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic
accidents worldwide and the number has been continuously increasing over the last few …
accidents worldwide and the number has been continuously increasing over the last few …
Deep transfer with minority data augmentation for imbalanced breast cancer dataset
Clinical diagnosis of breast cancer is a challenging problem in the biomedical domain. The
BreakHis breast cancer histopathological image dataset consists of two classes: Benign …
BreakHis breast cancer histopathological image dataset consists of two classes: Benign …
Driver anomaly quantification for intelligent vehicles: A contrastive learning approach with representation clustering
Driver anomaly quantification is a fundamental capability to support human-centric driving
systems of intelligent vehicles. Existing studies usually treat it as a classification task and …
systems of intelligent vehicles. Existing studies usually treat it as a classification task and …
HCF: A hybrid CNN framework for behavior detection of distracted drivers
C Huang, X Wang, J Cao, S Wang, Y Zhang - IEEE access, 2020 - ieeexplore.ieee.org
Distracted driving causes a large number of traffic accident fatalities and is becoming an
increasingly important issue in recent research on traffic safety. Gesture patterns are less …
increasingly important issue in recent research on traffic safety. Gesture patterns are less …
[HTML][HTML] Automatic driver distraction detection using deep convolutional neural networks
Recently, the number of road accidents has been increased worldwide due to the distraction
of the drivers. This rapid road crush often leads to injuries, loss of properties, even deaths of …
of the drivers. This rapid road crush often leads to injuries, loss of properties, even deaths of …
Toward extremely lightweight distracted driver recognition with distillation-based neural architecture search and knowledge transfer
The number of traffic accidents has been continuously increasing in recent years worldwide.
Many accidents are caused by distracted drivers, who take their attention away from driving …
Many accidents are caused by distracted drivers, who take their attention away from driving …
Brain tumor segmentation using cascaded deep convolutional neural network
Gliomas are the most common and threatening brain tumors with little to no survival rate.
Accurate detection of such tumors is crucial for survival of the subject. Naturally, tumors have …
Accurate detection of such tumors is crucial for survival of the subject. Naturally, tumors have …