Weighted Pseudo-Labels and Bounding Boxes for Semisupervised SAR Target Detection

Weighted Pseudo-Labels and Bounding Boxes for Semisupervised SAR Target Detection

Synthetic aperture radar (SAR) image target detection methods based on semisupervised learning, such as the mean teacher framework, have shown promise in diminishing the issue of limited labeled data. However, several challenges exist in current methods. First, data augmentation techniques designed...

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Bibliographic Details
Main Authors: Zhuangzhuang Tian, Wei Wang, Kai Zhou, Xiaoxiang Song, Yilong Shen, Shengqi Liu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural networks (CNNs)
deep learning
object detection
semisupervised learning
synthetic aperture radar (SAR)
Online Access:https://ieeexplore.ieee.org/document/10423785/

Internet

https://ieeexplore.ieee.org/document/10423785/

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