1 citations · 1 across the 7 of their papers we have counts for
8 papers
Weight Group-wise Post-Training Quantization for Medical Foundation Model
Yineng Chen, Peng Huang, Aozhong Zhang +9
Foundation models have achieved remarkable results in medical image analysis. However, its large network architecture and high computational complexity significantly impact inferen…
ReDiPrune: Relevance-Diversity Pre-Projection Token Pruning for Efficient Multimodal LLMs
An Yu, Ting Yu Tsai, Zhenfei Zhang +3
Recent multimodal large language models are computationally expensive because Transformers must process a large number of visual tokens. We present ReDiPrune, a training-free token…
RatSeizure: A Benchmark and Saliency-Context Transformer for Rat Seizure Localization
Ting Yu Tsai, An Yu, Lucy Lee +5
Animal models, particularly rats, play a critical role in seizure research for studying epileptogenesis and treatment response. However, progress is limited by the lack of datasets…
IntelliCardiac: An Intelligent Platform for Cardiac Image Segmentation and Classification
Ting Yu Tsai, An Yu, Meghana Spurthi Maadugundu +5
Precise and effective processing of cardiac imaging data is critical for the identification and management of the cardiovascular diseases. We introduce IntelliCardiac, a comprehens…
RLMiniStyler: Light-weight RL Style Agent for Arbitrary Sequential Neural Style Generation
Jing Hu, Chengming Feng, Shu Hu +4
Arbitrary style transfer aims to apply the style of any given artistic image to another content image. Still, existing deep learning-based methods often require significant computa…
LLaVA-MR: Large Language-and-Vision Assistant for Video Moment Retrieval
Weiheng Lu, Jian Li, An Yu +3
Multimodal Large Language Models (MLLMs) are widely used for visual perception, understanding, and reasoning. However, long video processing and precise moment retrieval remain cha…
An Uncertainty-Aware Generalization Framework for Cardiovascular Image Segmentation
Ting Yu Tsai, Liangqiao Gui, Yineng Chen +8
Deep learning models have achieved significant success in segmenting cardiovascular structures, but there is a growing need to improve their generalization and robustness. Current…
UU-Mamba: Uncertainty-aware U-Mamba for Cardiac Image Segmentation
Ting Yu Tsai, Li Lin, Shu Hu +3
Biomedical image segmentation is critical for accurate identification and analysis of anatomical structures in medical imaging, particularly in cardiac MRI. Manual segmentation is…