most citedGlobal in Local: A Convolutional Transformer for SAR ATR FSL

53 citations · 147 across the 14 of their papers we have counts for

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eess.IV2023

SAR ATR Method with Limited Training Data via an Embedded Feature Augmenter and Dynamic Hierarchical-Feature Refiner

Chenwei Wang, Siyi Luo, Yulin Huang +3

Without sufficient data, the quantity of information available for supervised training is constrained, as obtaining sufficient synthetic aperture radar (SAR) training data in pract…

eess.IV2023

Crucial Feature Capture and Discrimination for Limited Training Data SAR ATR

Chenwei Wang, Siyi Luo, Jifang Pei +3

Although deep learning-based methods have achieved excellent performance on SAR ATR, the fact that it is difficult to acquire and label a lot of SAR images makes these methods, whi…

eess.IV2023

An Entropy-Awareness Meta-Learning Method for SAR Open-Set ATR

Chenwei Wang, Siyi Luo, Jifang Pei +4

Existing synthetic aperture radar automatic target recognition (SAR ATR) methods have been effective for the classification of seen target classes. However, it is more meaningful a…

eess.IV2023

SAR Ship Target Recognition Via Multi-Scale Feature Attention and Adaptive-Weighed Classifier

Chenwei Wang, Jifang Pei, Siyi Luo +4

Maritime surveillance is indispensable for civilian fields, including national maritime safeguarding, channel monitoring, and so on, in which synthetic aperture radar (SAR) ship ta…

eess.IV2023

Unveiling Causalities in SAR ATR: A Causal Interventional Approach for Limited Data

Chenwei Wang, Xin Chen, You Qin +4

Synthetic aperture radar automatic target recognition (SAR ATR) methods fall short with limited training data. In this letter, we propose a causal interventional ATR method (CIATR)…

eess.IV2023★ 8 cited

A deep deformable residual learning network for SAR images segmentation

Chenwei Wang, Jifang Pei, Yulin Huang +1

Reliable automatic target segmentation in Synthetic Aperture Radar (SAR) imagery has played an important role in the SAR fields. Different from the traditional methods, Spectral Re…

eess.IV2023★ 33 cited

When Deep Learning Meets Multi-Task Learning in SAR ATR: Simultaneous Target Recognition and Segmentation

Chenwei Wang, Jifang Pei, Zhiyong Wang +4

With the recent advances of deep learning, automatic target recognition (ATR) of synthetic aperture radar (SAR) has achieved superior performance. By not being limited to the targe…

eess.IV2023★ 47 cited

SAR Target Image Generation Method Using Azimuth-Controllable Generative Adversarial Network

Chenwei Wang, Jifang Pei, Xiaoyu Liu +4

Sufficient synthetic aperture radar (SAR) target images are very important for the development of researches. However, available SAR target images are often limited in practice, wh…

eess.IV2023★ 53 cited

Global in Local: A Convolutional Transformer for SAR ATR FSL

Chenwei Wang, Yulin Huang, Xiaoyu Liu +3

Convolutional neural networks (CNNs) have dominated the synthetic aperture radar (SAR) automatic target recognition (ATR) for years. However, under the limited SAR images, the widt…

eess.IV2023

SAR Ship Target Recognition via Selective Feature Discrimination and Multifeature Center Classifier

Chenwei Wang, Siyi Luo, Jifang Pei +3

Maritime surveillance is not only necessary for every country, such as in maritime safeguarding and fishing controls, but also plays an essential role in international fields, such…

eess.IV2023★ 1 cited

Causal SAR ATR with Limited Data via Dual Invariance

Chenwei Wang, You Qin, Li Li +5

Synthetic aperture radar automatic target recognition (SAR ATR) with limited data has recently been a hot research topic to enhance weak generalization. Despite many excellent meth…

eess.IV2023★ 5 cited

SAR ATR under Limited Training Data Via MobileNetV3

Chenwei Wang, Siyi Luo, Lin Liu +4

In recent years, deep learning has been widely used to solve the bottleneck problem of synthetic aperture radar (SAR) automatic target recognition (ATR). However, most current meth…