An Unsupervised Snow Segmentation Approach Based on Dual-Polarized Scattering Mechanism and Deep Neural Network
Author:
Affiliation:
1. Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
2. Department of Electronic Engineering, Tsinghua University, Beijing, China
Funder
National Key Research and Development Program of China
International Partnership Program of Chinese Academy of Sciences
Science and Technology Basic Resources Investigation Program of China
Key Deployment Program of AIRCAS
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10006360/10083095.pdf?arnumber=10083095
Reference51 articles.
1. Four-component scattering model for polarimetric SAR image decomposition
2. Target Scattering Decomposition in Terms of Roll-Invariant Target Parameters
3. Identification of Snow Using Fully Polarimetric SAR Data Based On Entropy and Anisotropy
4. Dry and Wet Snow Cover Mapping in Mountain Areas Using SAR and Optical Remote Sensing Data
5. An entropy based classification scheme for land applications of polarimetric SAR
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