贺浩 王舒洋 王仕成 | 《测绘学报（英文版）》（JGGS）精选论文

Journal of Geodesy and Geoinformation Science

构建与学术的桥梁        拉近与权威的距离

🔷Title l 题目

A Road Extraction Method for Remote Sensing Image Based on Encoder-Decoder Network

🔷Citation l 引文格式

Hao HE, Shuyang WANG, Shicheng WANG, et al. A Road Extraction Method for Remote Sensing Image Based on Encoder-Decoder Network[J]. Journal of Geodesy and Geoinformation Science, 2020, 3(2): 16-25. DOI: 10.11947/ j.JGGS.2020.0202.

🔷Abstract l 摘要

According to the characteristics of the road features, an Encoder-Decoder deep semantic segmentation network is designed for the road extraction of remote sensing images. Firstly, as the features of the road target are rich in local details and simple in semantic features, an Encoder-Decoder network with shallow layers and high resolution is designed to improve the ability to represent detail information. Secondly, as the road area is a small proportion in remote sensing images, the cross-entropy loss function is improved, which solves the imbalance between positive and negative samples in the training process. Experiments on large road extraction datasets show that the proposed method gets the recall rate 83.9%, precision 82. 5% and F1-score 82.9%, which can extract the road targets in remote sensing images completely and accurately. The Encoder-Decoder network designed in this paper performs well in the road extraction task and needs less artificial participation, so it has a good application prospect. 

🔷Key words l 关键词

remote sensing; road extraction; deep learning; semantic segmentation; Encoder-Decoder network 

🔷About the Authors l 作者简介

Hao HE, Shuyang WANG, Shicheng WANG, Dongfang YANG, Xing LIU

• Hao HE
  

贺浩，男，1991年生，博士研究生，目前的研究方向为深度学习、遥感、机器学习与模式识别、道路提取，先后发表SCI、EI等论文十余篇。

• Shuyang WANG
  

王舒洋，女，1991年生，博士研究生，研究方向为遥感、计算机视觉、目标识别等。

• Shicheng WANG
  

王仕成，男，教授，博士生导师，长期致力于导航制导与控制、地磁等领域的教学与科研工作。获国家科技进步二等奖三项；公开发表学术论文150余篇，合作出版专著3部；曾获得中国科学协“求是”杰出青年实用工程奖；入选国家百千万人才工程。

🔷全文摘录如下

本文节选自JGGS 2020,Volume 3,Issue 2, p16-25

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