城市区域视觉地理定位的深度度量学习效率分析

2018 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF) Pub Date : 2018-11-01 DOI:10.1109/WECONF.2018.8604410

A. A. Kishkun, A. Veselov

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引用次数: 1

摘要

本文主要研究城市区域的视觉地理定位问题。提出了一种基于卷积神经网络(CNN)的识别方法。分析了一套深度度量学习算法，以提高识别性能。在ZuBuD数据集上的实验结果证明了将深度度量学习应用于视觉地理定位问题的好处。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Efficiency Analysis of Deep Metric Learning for Visual Geolocalisation in Urban Area

The paper is devoted to the problem of visual geolocalisation in an urban area. A method of building recognition based on convolutional neural networks (CNN) is proposed. A set of deep metric learning algorithms is analyzed to improve the recognition performance. Experimental results on ZuBuD dataset demonstrate the benefits of applying deep metric learning in the problem of visual geolocalisation.

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来源期刊

2018 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF)

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