UFCN: a fully convolutional neural network for road extraction in RGB imagery acquired by remote sensing from an unmanned aerial vehicle-Reference-Cited by-同舟云学术

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UFCN: a fully convolutional neural network for road extraction in RGB imagery acquired by remote sensing from an unmanned aerial vehicle

Published:2018-02-13 Issue:01 Volume:12 Page:1
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:
Short-container-title:J. Appl. Rem. Sens.

Author:

Kestur Ramesh¹,Farooq Shariq²,Abdal Rameen²,Mehraj Emad²,Narasipura Omkar³,Mudigere Meenavathi¹

Affiliation:

1. Bangalore Institute of Technology (BIT), Department of Electronics and Instrumentation Engineering,

2. National Institute of Technology (NIT), Department of Electronics and Communication Engineering, Sri

3. Indian Institute of Science (IISc), Department of Aerospace Engineering, Bangalore

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Earth and Planetary Sciences

Reference39 articles.

1. A review of road extraction from remote sensing images

2. A New Approach to Urban Road Extraction Using High-Resolution Aerial Image

3. Region-based urban road extraction from VHR satellite images using Binary Partition Tree

4. Assessing the global transport infrastructure market: outlook to 2025;Julian,2015

5. Transferring Deep Convolutional Neural Networks for the Scene Classification of High-Resolution Remote Sensing Imagery

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