计算机科学
面子(社会学概念)
人工智能
工件(错误)
噪音(视频)
计算机视觉
高级驾驶员辅助系统
图像(数学)
社会科学
社会学
作者
Abdellatif Moussaid,Ismaïl Berrada,Mohamed El Kamili,Khalid Fardousse
标识
DOI:10.1109/wincom47513.2019.8942531
摘要
In this paper, we will present our project concerning realizing a system of predicting maneuvers before the vehicle turns through using a dataset containing videos of drivers in different situations and different maneuvers, as well as information on the environment, such as speed, empty lines and the existence of an artifact. After preparing the dataset, we built our CNN-LSTM model based on convolutional and recurrent layers. Our CNN-LSTM model allowed us to predict the maneuver with an accuracy of 94.1% and 3.75 seconds before the turn. Finally, For our model to be robust, we tried to detect anomalies and replace them with more meaningful values. We also tested our model by adding noise to the images.
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