Dual Consistency Alignment Based Self-Supervised Learning for SAR Target Recognition With Speckle Noise Resistance-Reference-Cited by-同舟云学术

Dual Consistency Alignment Based Self-Supervised Learning for SAR Target Recognition With Speckle Noise Resistance

Published:2023 Issue: Volume:16 Page:3915-3928
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:

Zhai Yikui¹^ORCID,Liao Jinrui¹^ORCID,Sun Bing²^ORCID,Jiang Ziyi¹^ORCID,Ying Zilu¹^ORCID,Wang Wenqi¹^ORCID,Genovese Angelo³^ORCID,Piuri Vincenzo³^ORCID,Scotti Fabio³^ORCID

Affiliation:

1. Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China

2. School of Electronics and Information Engineering, Beihang University, Beijing, China

3. Department of Computer Science and Dipartimento di Informatica, Università Degli Studi di Milano, Milano, Italy

Funder

Key Research Projects for Universities of Guangdong Provincial Education Department

Basic and Applied Basic Research Foundation of Guangdong Province

Guangdong, Hong Kong, Macao

Greater Bay Area International Science and Technology Innovation Cooperation Project

Jiangmen City Basic and Applied Basic Research Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9973430/10103576.pdf?arnumber=10103576

Reference59 articles.

1. Multiple Feature Aggregation Using Convolutional Neural Networks for SAR Image-Based Automatic Target Recognition

2. SAR image classification using contrastive learning and pseudo-labels with limited data;wang;IEEE Geosci Remote Sens Lett,2022

3. Speckle-Noise-Invariant Convolutional Neural Network for SAR Target Recognition

4. Rotation Awareness Based Self-Supervised Learning for SAR Target Recognition With Limited Training Samples

5. SAR Automatic Target Recognition Based on Multiview Deep Learning Framework

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. Residual wave vision U-Net for flood mapping using dual polarization Sentinel-1 SAR imagery;International Journal of Applied Earth Observation and Geoinformation;2024-03

2. Synthetic Aperture Radar Target Recognition Based on Frequency-Domain-Assisted Dual-Stream Attention Hierarchical Deformable Convolutional Networks;2024

3. Difference-Focusing Fusion Decision Method: An Ensemble Learning Framework and Its Application in Improving Deep Learning Sea–Land Segmentation for Waterline Extraction in Synthetic Aperture Radar Imagery;IEEE Transactions on Geoscience and Remote Sensing;2024