53 citations · 147 across the 14 of their papers we have counts for
14 papers
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…
Semi-Supervised SAR ATR Framework with Transductive Auxiliary Segmentation
Chenwei Wang, Xiaoyu Liu, Yulin Huang +4
Convolutional neural networks (CNNs) have achieved high performance in synthetic aperture radar (SAR) automatic target recognition (ATR). However, the performance of CNNs depends h…
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…
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…
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…
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)…
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…
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…
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…
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…
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…
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…
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…
Controlled Remote State Preparation via General Pure Three-Qubit State
Zhi-Hua Zhang, Lan Shu, Jun Zheng
The protocols for controlled remote state preparation of a single qubit and a general two-qubit state are presented in this paper. The general pure three-qubit states are chosen as…