基于多方向图像投影的连体神经网络车辆图像匹配

2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2018-05-01 DOI:10.1109/SACI.2018.8440917

Gábor Kertész, S. Szénási, Z. Vámossy

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引用次数: 4

摘要

基于卷积神经网络的暹罗结构，提出了一种测量图像相似性的新方法。两个相同的cnn提取输入的重要部分，一个神经元输出两个的距离。本文的目的是介绍暹罗结构可以应用于基于图像投影的车辆特征匹配。

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

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.

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来源期刊

2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI)

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