A Novel Technique Based on Deep Learning and a Synthetic Target Database for Classification of Urban Areas in PolSAR Data-Reference-Cited by-同舟云学术

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A Novel Technique Based on Deep Learning and a Synthetic Target Database for Classification of Urban Areas in PolSAR Data

Published:2018-01 Issue:1 Volume:11 Page:154-170
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

De Shaunak^ORCID,Bruzzone Lorenzo^ORCID,Bhattacharya Avik^ORCID,Bovolo Francesca^ORCID,Chaudhuri Subhasis

Funder

Italian Ministries MAECI/MIUR

Advanced Research (ITPAR), Phase III

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/8262688/08068203.pdf?arnumber=8068203

Cited by 73 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. CNNs for remote extraction of urban features: A survey-driven benchmarking;Expert Systems with Applications;2024-12

2. DNN-PolSAR: Urban Image Segmentation and Classification using Polarimetric SAR based on DNNs;International Journal of Inventive Engineering and Sciences;2024-05-30

3. Data-driven polarimetric imaging: a review;Opto-Electronic Science;2024

4. Light image enhancement based on embedded image system application in animated character images;Optical and Quantum Electronics;2023-12-14

5. Polsar Image Classification Based on 3D Generative Adversarial Networks;2023 IEEE India Geoscience and Remote Sensing Symposium (InGARSS);2023-12-10

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