Open AccessRoad identification system based on CNN
Author(s) -
Xuebin Yang,
Hongzhi Yu,
Di Wang,
Ding Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1486/4/042024
Subject(s) - convolutional neural network , computer science , artificial intelligence , pixel , identification (biology) , computer vision , pattern recognition (psychology) , biology , botany
In recent years, convolutional neural network (CNN) has been widely used in image recognition, but there is still a big gap in automatic driving and road recognition. Here we have designed a system that maps raw pixels directly from a single front-facing camera to a steering command. The system mainly uses the camera to recognize the auxiliary lines on the road to realize automatic driving, and the accuracy rate has reached 98%. Unfortunately, such data can only be used in the laboratory, and the recognition of complex road conditions needs further development of machine learning.