Extracting multi-features and optimizing feature space with sparse auto-encoder over WorldView-2 images-Reference-Cited by-同舟云学术

Extracting multi-features and optimizing feature space with sparse auto-encoder over WorldView-2 images

Published:2019-03-26 Issue:16 Volume:40 Page:6418-6443
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Yang Dehe¹^ORCID,Lv Jingguo²,Zhang Danlu²,Zhang Jingfa¹,Yuan Jing³

Affiliation:

1. Key Laboratory of Crustal Dynamics, Institute of Crustal Dynamics, China Earthquake Administration, Beijing, China

2. Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China

3. Institute of Disaster Prevention, School of Information Engineering, Sanhe, Hebei, China

Funder

Beijing Natural Science Foundation

National Natural Science Foundation of China

Beijing Advanced Innovation Center for Future Urban Design

Scientific Research Project of Beijing Educational Committee

Beijing Key Laboratory of Urban Spatial Information Engineering

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2019.1594431

Reference57 articles.

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2. Remote Sensing of Urban Microclimate Change in L’Aquila City (Italy) after Post-Earthquake Depopulation in an Open Source GIS Environment

3. Fast wrapper feature subset selection in high-dimensional datasets by means of filter re-ranking

4. Geographic Object-Based Image Analysis – Towards a new paradigm

5. Optimal segmentation of a high-resolution remote-sensing image guided by area and boundary

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