Scene classification for remote sensing image of land use and land cover using dual-model architecture with multilevel feature fusion-Reference-Cited by-同舟云学术

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Scene classification for remote sensing image of land use and land cover using dual-model architecture with multilevel feature fusion

Published:2024-05-17 Issue:1 Volume:17 Page:
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Guo Ningbo¹^ORCID,Jiang Mingyong¹,Wang Decheng²^ORCID,Zhou Xixuan¹,Song Zekao³,Li Yinan¹,Gao Lijing⁴,Luo JianCheng⁴

Affiliation:

1. School of Space Information, Space Engineering University, Beijing, People’s Republic of China

2. Beijing Institute of Tracking and Telecommunication Technology, Beijing, People’s Republic of China

3. Remote Sensing Institute, Beijing, People’s Republic of China

4. State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of China

Funder

Internal Parenting Program

National Natural Science Foundation of China

Space Engineering University

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2024.2353166

Reference52 articles.

1. Review of deep learning methods for remote sensing satellite images classification: experimental survey and comparative analysis

2. RS-DeepSuperLearner: fusion of CNN ensemble for remote sensing scene classification

3. Classification of Remote Sensing Images Using EfficientNet-B3 CNN Model With Attention

4. Data Augmentation in Classification and Segmentation: A Survey and New Strategies

5. Vision Transformers for Remote Sensing Image Classification

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