Analysis of similar object classification performance of deep neural network-based object recognition technique

被引:0
作者
Kim S.-H. [1 ]
机构
[1] Division of Aeronautics, Cheongju University
关键词
Armored Fighting Vehicle; Deep Neural Networks; DenseNet; ResNet; Smart Factory;
D O I
10.5302/J.ICROS.2021.21.0113
中图分类号
学科分类号
摘要
In this study, deep neural networks were applied to a similar object classification method, and the classification performance was analyzed. For the similar object classification performance analysis, ResNet50 and DenseNet169 models, which are known to show similar behaviors, were selected. To verify the performance of these deep neural networks, a bolt recognition for smart factories and an armored fighting vehicle recognition were performed. In addition, image preprocessing methods to improve the similar object classification performance were proposed. The experimental results confirmed that appropriate image preprocessing methods should be applied according to the type of similar object to be classified. © ICROS 2021.
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页码:858 / 863
页数:5
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