5 papers
MedAD-R1: Eliciting Consistent Reasoning in Interpretible Medical Anomaly Detection via Consistency-Reinforced Policy Optimization
Haitao Zhang, Yingying Wang, Jiaxiang Wang +5
Medical Anomaly Detection (MedAD) presents a significant opportunity to enhance diagnostic accuracy using Large Multimodal Models (LMMs) to interpret and answer questions based on…
Pan-LUT: Efficient Pan-sharpening via Learnable Look-Up Tables
Zhongnan Cai, Yingying Wang, Hui Zheng +10
Recently, deep learning-based pan-sharpening algorithms have achieved notable advancements over traditional methods. However, deep learning-based methods incur substantial computat…
Bridging Synthetic-to-Real Gaps: Frequency-Aware Perturbation and Selection for Single-shot Multi-Parametric Mapping Reconstruction
Linyu Fan, Che Wang, Ming Ye +7
Data-centric artificial intelligence (AI) has remarkably advanced medical imaging, with emerging methods using synthetic data to address data scarcity while introducing synthetic-t…
PCMamba: Physics-Informed Cross-Modal State Space Model for Dual-Camera Compressive Hyperspectral Imaging
Ge Meng, Zhongnan Cai, Jingyan Tu +4
Panchromatic (PAN) -assisted Dual-Camera Compressive Hyperspectral Imaging (DCCHI) is a key technology in snapshot hyperspectral imaging. Existing research primarily focuses on exp…
FRN: Fractal-Based Recursive Spectral Reconstruction Network
Ge Meng, Zhongnan Cai, Ruizhe Chen +4
Generating hyperspectral images (HSIs) from RGB images through spectral reconstruction can significantly reduce the cost of HSI acquisition. In this paper, we propose a Fractal-Bas…