5 papers · 1 filter
PCM-SAR: Physics-Driven Contrastive Mutual Learning for SAR Classification
Pengfei Wang, Hao Zheng, Zhigang Hu +3
Existing SAR image classification methods based on Contrastive Learning often rely on sample generation strategies designed for optical images, failing to capture the distinct sema…
ElimPCL: Eliminating Noise Accumulation with Progressive Curriculum Labeling for Source-Free Domain Adaptation
Jie Cheng, Hao Zheng, Meiguang Zheng +3
Source-Free Domain Adaptation (SFDA) aims to train a target model without source data, and the key is to generate pseudo-labels using a pre-trained source model. However, we observ…
Dual-stream contrastive predictive network with joint handcrafted feature view for SAR ship classification
Xianting Feng, Hao zheng, Zhigang Hu +2
Most existing synthetic aperture radar (SAR) ship classification technologies heavily rely on correctly labeled data, ignoring the discriminative features of unlabeled SAR ship ima…
MetaDefa: Meta-learning based on Domain Enhancement and Feature Alignment for Single Domain Generalization
Can Sun, Hao Zheng, Zhigang Hu +3
The single domain generalization(SDG) based on meta-learning has emerged as an effective technique for solving the domain-shift problem. However, the inadequate match of data distr…
Double Reverse Regularization Network Based on Self-Knowledge Distillation for SAR Object Classification
Bo Xu, Hao Zheng, Zhigang Hu +2
In current synthetic aperture radar (SAR) object classification, one of the major challenges is the severe overfitting issue due to the limited dataset (few-shot) and noisy data. C…