A Deep-Learning Approach for SAR Tomographic Imaging of Forested Areas-Reference-Cited by-同舟云学术

A Deep-Learning Approach for SAR Tomographic Imaging of Forested Areas

Author:

Berenger Zoé¹^ORCID,Denis Loïc²^ORCID,Tupin Florence¹^ORCID,Ferro-Famil Laurent³^ORCID,Huang Yue⁴^ORCID

Affiliation:

1. LTCI, Télécom Paris, Institut Polytechnique de Paris, Palaiseau, France

2. Laboratoire Hubert Curien, UMR 5516, CNRS, Institut d’Optique Graduate School, Université de Lyon, UJM-Saint-Étienne, Saint-Étienne, France

3. ISAE-SUPAERO and CESBIO, University of Toulouse, Toulouse, France

4. CESBIO, University of Toulouse, Toulouse, France

Funder

Futur and Ruptures Ph.D. Program of the Fondation Mines-Telecom

project ASTRAL

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

Reference17 articles.

3. BIOSAR 2008 technical assistance for the development of airborne SAR and geophysical measurements during the BioSAR 2008 experiment;hajnsek,2009

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