Deep feature learning versus shallow feature learning systems for joint use of airborne thermal hyperspectral and visible remote sensing data-Reference-Cited by-同舟云学术

Deep feature learning versus shallow feature learning systems for joint use of airborne thermal hyperspectral and visible remote sensing data

Published:2019-03-28 Issue:18 Volume:40 Page:7048-7070
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Bigdeli Behnaz¹,Amini Amirkolaee Hamed²,Pahlavani Parham²

Affiliation:

1. Department of Civil Engineering, Shahrood University of Technology, Shahrood, Iran

2. Center of Excellence in Geomatics Engineering in Disaster Management, Department of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2019.1597310

Reference27 articles.

1. Feature grouping-based multiple fuzzy classifier system for fusion of hyperspectral and LIDAR data

2. High resolution multisensor fusion of SAR, optical and LiDAR data based on crisp vs. fuzzy and feature vs. decision ensemble systems

3. Quad-polarized synthetic aperture radar and multispectral data classification using classification and regression tree and support vector machine–based data fusion system

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