Dual-Branch Sparse Self-Learning With Instance Binding Augmentation for Adversarial Detection in Remote Sensing Images-Reference-Cited by-同舟云学术

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Dual-Branch Sparse Self-Learning With Instance Binding Augmentation for Adversarial Detection in Remote Sensing Images

Published:2024 Issue: Volume:62 Page:1-13
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zhang Zhentong¹^ORCID,Li Xinde²^ORCID,Li Heqing¹^ORCID,Dunkin Fir³^ORCID,Li Bing³^ORCID,Li Zhijun⁴^ORCID

Affiliation:

1. School of Cyber Science and Engineering, Southeast University, Nanjing, China

2. Nanjing Center for Applied Mathematics, Nanjing, China

3. School of Automation, Southeast University, Nanjing, China

4. School of Mechanical Engineering, Translational Research Center, and Shanghai Yangzhi Rehabilitation Hospital, Tongji University, Shanghai, China

Funder

National Natural Science Foundation of China

Key Projects of Key Research and Development Program of Jiangsu Province

Shenzhen Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/36/10354519/10620338.pdf?arnumber=10620338

Reference57 articles.

1. A Neural Network-Based Atmospheric Correction Algorithm for GOCI Imagery Over Coastal Waters

2. Multiscale Attention Fusion Graph Network for Remote Sensing Building Change Detection

3. Review on Convolutional Neural Networks (CNN) in vegetation remote sensing

4. UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery

5. Building Damage Detection Using U-Net with Attention Mechanism from Pre- and Post-Disaster Remote Sensing Datasets

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