1 citations · 1 across the 4 of their papers we have counts for
6 papers · 1 filter
SARATR-X-v2: Scale-Aware Structural Pre-Training for SAR Foundation Models
Weijie Li, Yafei Song, Yongxiang Liu +7
Masked image modeling has become a dominant paradigm for SAR pre-training, yet the design of the reconstruction target remains fundamentally unsettled. This article argues that a S…
Light-ResKAN: A Parameter-Sharing Lightweight KAN with Gram Polynomials for Efficient SAR Image Recognition
Pan Yi, Weijie Li, Xiaodong Chen +3
Synthetic Aperture Radar (SAR) image recognition is vital for disaster monitoring, military reconnaissance, and ocean observation. However, large SAR image sizes hinder deep learni…
ATRNet-STAR: A Large Dataset and Benchmark Towards Remote Sensing Object Recognition in the Wild
Yongxiang Liu, Weijie Li, Li Liu +8
The absence of publicly available, large-scale, high-quality datasets for Synthetic Aperture Radar Automatic Target Recognition (SAR ATR) has significantly hindered the application…
Enhancing Transferability of Targeted Adversarial Examples: A Self-Universal Perspective
Bowen Peng, Li Liu, Tianpeng Liu +2
Transfer-based targeted adversarial attacks against black-box deep neural networks (DNNs) have been proven to be significantly more challenging than untargeted ones. The impressive…
Cross Domain Object Detection via Multi-Granularity Confidence Alignment based Mean Teacher
Jiangming Chen, Li Liu, Wanxia Deng +4
Cross domain object detection learns an object detector for an unlabeled target domain by transferring knowledge from an annotated source domain. Promising results have been achiev…
Towards Assessing the Synthetic-to-Measured Adversarial Vulnerability of SAR ATR
Bowen Peng, Bo Peng, Jingyuan Xia +3
Recently, there has been increasing concern about the vulnerability of deep neural network (DNN)-based synthetic aperture radar (SAR) automatic target recognition (ATR) to adversar…