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Feature Analysis and Selection for Training an End-to-End Autonomous
  Vehicle Controller Using the Deep Learning Approach

Feature Analysis and Selection for Training an End-to-End Autonomous Vehicle Controller Using the Deep Learning Approach

28 March 2017
Shun Yang
Wenshuo Wang
Chang-rui Liu
W. Deng
J. Hedrick
ArXivPDFHTML

Papers citing "Feature Analysis and Selection for Training an End-to-End Autonomous Vehicle Controller Using the Deep Learning Approach"

4 / 4 papers shown
Title
Incorporating Orientations into End-to-end Driving Model for Steering
  Control
Incorporating Orientations into End-to-end Driving Model for Steering Control
Peng Wan
Zhenbo Song
Jianfeng Lu
LLMSV
23
0
0
10 Mar 2021
Multi-modal Sensor Fusion-Based Deep Neural Network for End-to-end
  Autonomous Driving with Scene Understanding
Multi-modal Sensor Fusion-Based Deep Neural Network for End-to-end Autonomous Driving with Scene Understanding
Zhiyu Huang
Chen Lv
Yang Xing
Jingda Wu
11
128
0
19 May 2020
A Survey of Deep Learning Applications to Autonomous Vehicle Control
A Survey of Deep Learning Applications to Autonomous Vehicle Control
Sampo Kuutti
Richard Bowden
Yaochu Jin
P. Barber
Saber Fallah
36
506
0
23 Dec 2019
Extracting Traffic Primitives Directly from Naturalistically Logged Data
  for Self-Driving Applications
Extracting Traffic Primitives Directly from Naturalistically Logged Data for Self-Driving Applications
Wenshuo Wang
Ding Zhao
AI4TS
20
74
0
11 Sep 2017
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