18 citations · 37 across the 10 of their papers we have counts for
11 papers
T-JEPA: A Temporal Joint-Embedding Predictive Architecture for Learning Better Remote Sensing Representations
Bowen Peng, Li Liu, Yongxiang Liu +3
Earth observation (EO) data provide rich temporal supervision, yet existing remote sensing foundation models mainly exploit sequential observations through imposing predefined pair…
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…
Fifty Years of SAR Automatic Target Recognition: The Road Forward
Jie Zhou, Yongxiang Liu, Li Liu +6
Synthetic Aperture Radar (SAR) imaging is capable of observing objects in nearly all weather and illumination conditions, and has become an indispensable means of information acqui…
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…
MaDiNet: Mamba Diffusion Network for SAR Target Detection
Jie Zhou, Chao Xiao, Bowen Peng +4
The fundamental challenge in SAR target detection lies in developing discriminative, efficient, and robust representations of target characteristics within intricate non-cooperativ…
SST: A Strong, Self-transferable, faSt, and Simple Scale Transformation for Transferable Targeted Attack
Yongxiang Liu, Bowen Peng, Li Liu +1
Transferable Targeted Attacks (TTAs) face significant challenges due to severe overfitting to surrogate models. Recent breakthroughs heavily rely on large-scale training data of vi…
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…
ARBiBench: Benchmarking Adversarial Robustness of Binarized Neural Networks
Peng Zhao, Jiehua Zhang, Bowen Peng +4
Network binarization exhibits great potential for deployment on resource-constrained devices due to its low computational cost. Despite the critical importance, the security of bin…