A Case Study on Scene Recognition Using an Ensemble Convolution Neural Network

被引：0
作者：
Oh, Bongjin [1 ]
Lee, Junhyeok [2 ]
机构：
[1] ETRI, Software Contents Lab, Daejeon, South Korea
[2] KPST, Dept Res, Daejeon, South Korea
来源：
2018 20TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT) | 2018年
关键词：
scene recognition; ensemble deep neural network; object detection; convolution neural network; deep learning;
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：
this paper proposes architecture to recognize scene images based on an ensemble of two convolution neural networks. A convolution neural network is used to train massive scene images, and the other convolution neural network is used to extract objects from the scene images. The object lists are stored according to scene classes, and used as a clue to decide the top-1 and top-5 classes during scene image recognition stage.
引用
收藏
页码：351 / 353
页数：3
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