Comparison of Machine Learning Algorithm's Performance Based on Decision making in Autonomous Car

被引:0
|
作者
Thammachantuek, Ittikon [1 ]
Kosolsomnbat, Somkiat [2 ]
Ketcham, Mahasak [1 ]
机构
[1] King Mongkuts Univ Technol North Bangkok, ITMRC, Fac Informat Technol, Bangkok, Thailand
[2] Thammasat Univ, Fac Sci & Technol, Dept Data Sci & Innovat, Pathum Thani, Thailand
关键词
Autonomous car; Machine Learning; ML; Model prediction;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents the performance comparison of popular supervised learning algorithms: SVM, MLP, CNN, DT, and RF. These algorithms are used for road images recognition. All images are collected by our model car. They are labeled with four different classes: left, right, forward and stop. We use 90% of them for training and use 10% for testing each model. The result shows that, CNN has the best accuracy about 83.45%.
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页码:114 / 119
页数:6
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