Table1gives an overview of the characteristics of the frequently cited datasets for driver monitoring and the introduced dataset. Most datasets have notably been created to identify specific, limited factors, such as drowsiness. However, various driver state factors, including attention, workload, and ...
Several experiments are conducted on a public large-scale driver distraction dataset to evaluate the two models. The experimental results show that the accuracy rates were 99.64% for the first model and 99.73% for the second model using a holdout test set of 10%. In addition, the first and...
This project helps to detect the drowsiness of the driver.
Because OOB data are not involved in the building of the tree, the weight learning from this dataset can avoid over-fitting [45]. We can repeat the above procedure to generate the T′T′ decision trees and the accuracy values of the remaining trees are utilized as the weights 𝑤𝑡wt....
In contrast, the signs for a driver in the non-drowsiness or awake status drivers are non-yawning or open eyes. In this research, two datasets are accessed and collated for the experiment to detect the driver’s status. The first dataset is the yawning detection dataset (YawDD) [50], ...
drowsiness-dataset yawn-eye-dataset-new Tags GPU Language Python Table of Contents Drowsiness Detection System Collaborators NithishM2410 (Owner) dk_here (Editor) License This Notebook has been released under the Apache 2.0 open source license. Continue exploring Input4 files arrow_right_alt Output...
Explore and run machine learning code with Kaggle Notebooks | Using data from Driver Drowsiness Dataset (DDD)
As part of this project, the following dataset was created. The dataset contains images taken while driving a vehicle. This is done in two cases: some images show bus drivers without using a phone, just driving. In contrast, other samples show drivers while using a phone. The images were ...
StateFarm's Distracted Driver Detection Dataset. Available online: https://www.kaggle.com/c/state-farm- distracted-driver-detection (accessed on 13 February 2019). 39. Carreira, J.; Zisserman, A. Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset. In Proceedings of the ...
4.3.1. State Farm Distracted Driver Detection (SFD3) Dataset The State Farm Insurance (SFI) company published a challenging dataset of distracted drivers, which is publicly available on the Kaggle competition. The SFD3 contains around 102,150 images of different driver behaviors that are separated...