4 papers
Semantic Smoothing via Novel View Synthesis for Robust SAR Image Classification
Daniel Brignac, Fengwei Tian, Banafsheh Latibari +2
Deep neural networks are vulnerable to adversarial perturbations, limiting deployment in safety-critical applications such as synthetic aperture radar (SAR) automatic target recogn…
Pay Attention to Where You Looked
Alex Berian, JhihYang Wu, Daniel Brignac +2
Novel view synthesis (NVS) has advanced with generative modeling, enabling photorealistic image generation. In few-shot NVS, where only a few input views are available, existing me…
Is Mamba Reliable for Medical Imaging?
Banafsheh Saber Latibari, Najmeh Nazari, Daniel Brignac +3
State-space models like Mamba offer linear-time sequence processing and low memory, making them attractive for medical imaging. However, their robustness under realistic software a…
CrossModalityDiffusion: Multi-Modal Novel View Synthesis with Unified Intermediate Representation
Alex Berian, Daniel Brignac, JhihYang Wu +2
Geospatial imaging leverages data from diverse sensing modalities-such as EO, SAR, and LiDAR, ranging from ground-level drones to satellite views. These heterogeneous inputs offer…