Feasibility Study for the virtual Training and Testing of Artificial Neural Networks

被引：0

作者：

Kehrer, Martin ^{[1
]}

Hisung, Matthias ^{[1
]}

Reuss, Hans-Christian ^{[1
]}

机构：

[1] Univ Stuttgart, IVK, Stuttgart, Germany

来源：

AUTOREG 2017: AUTOMATISIERTES FAHREN UND VERNETZTE MOBILITAT | 2017年 / 2292卷

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, the feasibility of virtual training and testing of neural networks is investigated. Therefore a corresponding software framework and existing hardware infrastructure has been established to allow the integration of various types of sensors and development platforms at different system levels. The engines are used to generate the synthetic database: OpenSceneGraph and unreal Engine 4. Though the usage of a converter the objects can be exchanges between both engines. based on the neural networks SegNet and ENet the usefulness and the range of application will be examined.

引用

页码：491 / 500

页数：10

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