1 citations · 1 across the 1 of their papers we have counts for
4 papers
fMRI-LM: Towards a Universal Foundation Model for Language-Aligned fMRI Understanding
Yuxiang Wei, Yanteng Zhang, Xi Xiao +3
Recent advances in multimodal large language models (LLMs) have enabled unified reasoning across images, audio, and video, but extending such capability to brain imaging remains la…
Encoding Structural Constraints into Segment Anything Models via Probabilistic Graphical Models
Yu Li, Da Chang, Xi Xiao
While the Segment Anything Model (SAM) has achieved remarkable success in image segmentation, its direct application to medical imaging remains hindered by fundamental challenges,…
Boosting Active Learning with Knowledge Transfer
Tianyang Wang, Xi Xiao, Gaofei Chen +3
Uncertainty estimation is at the core of Active Learning (AL). Most existing methods resort to complex auxiliary models and advanced training fashions to estimate uncertainty for u…
TASAM: Terrain-and-Aware Segment Anything Model for Temporal-Scale Remote Sensing Segmentation
Tianyang Wang, Xi Xiao, Gaofei Chen +4
Segment Anything Model (SAM) has demonstrated impressive zero-shot segmentation capabilities across natural image domains, but it struggles to generalize to the unique challenges o…