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Author:

Zhao, Yuanfang (Zhao, Yuanfang.) | Chen, Yunli (Chen, Yunli.)

Indexed by:

EI

Abstract:

In the control algorithm of autopilot system, the Deep Learning method plays a vital role. Since the convolutional neural network (CNN) model used in automatic driving has a huge amount of parameters and the training results are prone to overfitting, an excellent model is necessary. In this paper, an end-to-end control method was proposed to apply a convolutional neural network with a new network structure to control the steering angle and speed of the vehicle and reach the goal of automatic vehicle driving. The experimental results show that it not only greatly reduces the number of parameters, but also keeps the error rate of the experimental results at the low level. © 2019 IEEE.

Keyword:

Convolutional neural networks Convolution Deep learning Learning systems Automobile drivers

Author Community:

  • [ 1 ] [Zhao, Yuanfang]Beijing University of Technology, Beijing, China
  • [ 2 ] [Chen, Yunli]Beijing University of Technology, Beijing, China

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Source :

Year: 2019

Page: 419-423

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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