Transfer Learning of Spatial Features From High-Resolution RGB Images for Large-Scale and Robust Hyperspectral Remote Sensing Target Detection-Reference-Cited by-同舟云学术

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Transfer Learning of Spatial Features From High-Resolution RGB Images for Large-Scale and Robust Hyperspectral Remote Sensing Target Detection

Published:2024 Issue: Volume:62 Page:1-32
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Wu Yuanfeng¹^ORCID,Li Zijin¹^ORCID,Zhao Boya¹^ORCID,Song Yuhang²,Zhang Bing²^ORCID

Affiliation:

1. Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

2. Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10402099.pdf?arnumber=10402099

Reference57 articles.

1. Imaging Spectrometry for Earth Remote Sensing

2. Advancement of hyperspectral image processing and information extraction;Zhang;J. Remote Sens.,1985

3. Progress and future of remote sensing data fusion;Zhang;J. Remote Sens.,2006

4. Progress and Challenges in Intelligent Remote Sensing Satellite Systems

Cited by 1 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. Renormalized Connection for Scale-Preferred Object Detection in Satellite Imagery;IEEE Transactions on Geoscience and Remote Sensing;2024

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