Optimization and Regularization Techniques in Androcar Design

被引:0
|
作者
Parlak, Cevahir [1 ]
Gurgen, Fikret [1 ]
机构
[1] Bogazici Univ, Bilgisayar Muhendisligi, TR-34342 Bebek, Turkey
关键词
androcars; robocars; self driving cars; autonomous cars; convolutional neural networks; computer vision; optimization; regularization;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Despite their prolonged history, Androcars (Robocars, Self Driving Cars, Autonomous Cars) only until recent decades gained substantial advances in parallel to the developments in computer vision and machine learning applications. In particular, we saw striking developments in the last twenty years. Today androcars are running their test drives on the public roads. In this text, we discuss the effect of different optimization and regularization techniques in convolutional neural networks applied to androcar design.
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页数:4
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