collaborators

5 papers

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

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…