An Object-Oriented CNN Model Based on Improved Superpixel Segmentation for High-Resolution Remote Sensing Image Classification-Reference-Cited by-同舟云学术

An Object-Oriented CNN Model Based on Improved Superpixel Segmentation for High-Resolution Remote Sensing Image Classification

Published:2022 Issue: Volume:15 Page:4782-4796
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:

Li Zhiqing¹^ORCID,Li Erzhu¹^ORCID,Samat Alim²^ORCID,Xu Tianyu¹^ORCID,Liu Wei¹^ORCID,Zhu Yihu³

Affiliation:

1. School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou, China

2. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China

3. Jiangsu Geologic Surveying and Mapping Institute, Nanjing, China

Funder

National Natural Science Foundation of China

Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences

Xuzhou Science and Technology Key R&D Program

Jiangsu Province Land and Resources Science and Technology Plan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

Reference75 articles.

1. Classification and regression by randomForest;liaw;R News,2002

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