| 作成者 |
|
|
|
|
|
|
|
|
|
|
|
| 本文言語 |
|
| 出版者 |
|
|
|
| 発行日 |
|
| 収録物名 |
|
| 巻 |
|
| 号 |
|
| 開始ページ |
|
| 終了ページ |
|
| 出版タイプ |
|
| アクセス権 |
|
| Crossref DOI |
|
| 権利関係 |
|
| 概要 |
Road accidents are the main cause of death among the human population. Distracted and drowsy driving takes thousands of lives every year around the world. Subsequently, to forestall such mishaps and s...ave lives, there is a requirement for a system that detects both distraction and drowsiness for both day and night time. In this paper, we present a deep learning convolutional model to detect distraction and drowsiness during driving. The proposed model performs real-time video processing for monitoring the activities of drivers during driving. The model produces an alert in case of any careless driving or inappropriate behaviour of the driver with the minimum response time. For this purpose dataset for training as well as for testing were prepared. For training the model, we have used CNN model. The proposed model was able to achieve 99.95% accuracy on test dataset.続きを見る
|
Mendeley出力
