74 citations · 110 across the 10 of their papers we have counts for
7 papers · 1 filter
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…
MMATR-X: High-Resolution Optical-SAR Joint Pretraining via Conditioned Alignment and Degraded-Target Prediction
Bowen Peng, Yongxiang Liu, Jie Zhou +4
Joint optical and Synthetic Aperture Radar (SAR) pretraining seeks cross-modal gains over representations learned from either modality alone. This is challenging because the modali…
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…
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…