Vehicle Image Matching using Siamese Neural Networks with Multi-Directional Image Projections

被引：0

作者：

Kertesz, Gabor ^{[1
]}

Szenasi, Sandor ^{[1
]}

Vamossy, Zoltan ^{[1
]}

机构：

[1] Obuda Univ, John von Neumann Fac Informat, Budapest, Hungary

来源：

2018 IEEE 12TH INTERNATIONAL SYMPOSIUM ON APPLIED COMPUTATIONAL INTELLIGENCE AND INFORMATICS (SACI) | 2018年

关键词：

MODEL;

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：

A novel method to measure similarity on images is based on the Siamese architecture of Convolutional Neural Networks. Two identical CNNs extract the significant parts of the inputs, and a single neuron outputs the distance of the two. The aim of this paper is to introduce that the Siamese structure can be applied to match image projection based signatures of vehicles.

引用

页码：491 / 496

页数：6

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