Deep Learning Approach To Update Road Network using VGI Data

被引：0

作者：

Manandhar, Prajowal ^{[1
]}

Marpu, Prashanth Reddy ^{[1
]}

Aung, Zeyar ^{[2
]}

机构：

[1] Khalifa Univ, Dept Elect & Comp Engn, Abu Dhabi, U Arab Emirates

[2] Khalifa Univ, Dept Comp Sci, Abu Dhabi, U Arab Emirates

来源：

2018 INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND INFORMATION SECURITY (ICSPIS) | 2018年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In our earlier work, we worked on extraction of the total width of road by agents traversing in the direction guided by Volunteered Geographic Information (VGI). The only downfall of VGI approach is its inability to update the new road developments. In this paper, we introduce deep learning approach to update the road network. We make use of the output of our previous work which forms as an input to train the Convolutional Neural Network (CNN). Then, further post processing is performed to remove non- road segments (such as buildings, vegetation, etc) on the output of CNN and finally, obtain the updated road map.

引用

页码：17 / 20

页数：4

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