In recent years, due to the rapid development of deep learning, the application of deep learning in the field of unmanned vehicle driving has achieved good results through a large number of experiments. First of all,this paper introduces the development of driverless technology at home and abroad, then it introduces the theoretical basis of deep learning. The aim is to give readers a quick look at the history and current status of driverless technology and readers can understand the importance of deep learning in the field of driverless technology at the same time. Secondly, this paper introduced different intelligent scene recognition and compared them to find out which technology is more suitable for the current situation. Finally, the paper proposes the optimization scheme that can be improved or improved according to the shortcomings of the intelligent scene recognition technology and the problems and the development prospects of intelligent vehicles.
CITATION STYLE
Ma, C. (2020). Application of Deep Learning in Vehicle Driverless Technology. In Journal of Physics: Conference Series (Vol. 1682). IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/1682/1/012071
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