Hybrid FusionNet: A Hybrid Feature Fusion Framework for Multisource High-Resolution Remote Sensing Image Classification-Reference-Cited by-同舟云学术

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Hybrid FusionNet: A Hybrid Feature Fusion Framework for Multisource High-Resolution Remote Sensing Image Classification

Published:2024 Issue: Volume:62 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zheng Yongjie¹^ORCID,Liu Sicong²^ORCID,Chen Hao³^ORCID,Bruzzone Lorenzo¹^ORCID

Affiliation:

1. Department of Information Engineering and Computer Science, University of Trento, Trento, Italy

2. College of Surveying and Geoinformatics, Tongji University, Shanghai, China

3. Institute of Geodesy and Geoinformation Science, Technische Universität Berlin, Berlin, Germany

Funder

National Natural Science Foundation of China

Shanghai Rising-Star Program

Research Project of Tongji Architectural Design (Group) Company Ltd.

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10398878.pdf?arnumber=10398878

Reference46 articles.

1. Unsupervised-Restricted Deconvolutional Neural Network for Very High Resolution Remote-Sensing Image Classification

2. A Novel Multitemporal Deep Fusion Network (MDFN) for Short-Term Multitemporal HR Images Classification

3. A Novel Feature Fusion Approach for VHR Remote Sensing Image Classification

4. Recurrent Multiresolution Convolutional Networks for VHR Image Classification

5. Unsupervised Spatial–Spectral Feature Learning by 3D Convolutional Autoencoder for Hyperspectral Classification

Cited by 3 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. Dilated Deep MPFormer Network for Hyperspectral Image Classification;IEEE Geoscience and Remote Sensing Letters;2024

2. Explainable Multimodal Learning in Remote Sensing: Challenges and Future Directions;IEEE Geoscience and Remote Sensing Letters;2024

3. Clear: A Novel Gap-Filling Method for Optical Remote Sensing Images Combining Class-Based Linear Regression and Iterative Residual Compensation;2024

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