2 citations · 4 across the 11 of their papers we have counts for
6 papers · 1 filter
Topology-Aware Parameter-Efficient Adaptation for Cross-Dataset Retinal Vessel Segmentation
Yongsong Huang, Tomo Miyazaki, Kai Xu +3
Retinal vessel segmentation in multi-domain deployment requires a source model to adapt to domains that differ in imaging conditions and annotation conventions. Conventional parame…
OGG-FR: Orthogonal Gradient Gaming and Frequency Rectification for Unmanned Aerial Vehicle Infrared Image Super-Resolution
Yongsong Huang, Qingzhong Wang, Xiaofeng Liu +3
Unmanned aerial vehicle (UAV) infrared image super-resolution aims to recover weak thermal structures for deployment on resource-constrained platforms; lightweight models are there…
Right Answer, Wrong Heat: Explanation-Aware Evaluation and Thermal-Grounded Feedback for MLLMs on Infrared Images
Yongsong Huang, Xiaofeng Liu, Tomo Miyazaki +2
General-purpose multimodal large language models (MLLMs) are increasingly applied to infrared images, where they are commonly scored by answer accuracy alone. However, a correct an…
Multimodal MRI Report Findings Supervised Brain Lesion Segmentation with Substructures
Yubin Ge, Yongsong Huang, Xiaofeng Liu
Report-supervised (RSuper) learning seeks to alleviate the need for dense tumor voxel labels with constraints derived from radiology reports (e.g., volumes, counts, sizes, location…
GTFMN: Guided Texture and Feature Modulation Network for Low-Light Image Enhancement and Super-Resolution
Yongsong Huang, Tzu-Hsuan Peng, Tomo Miyazaki +4
Low-light image super-resolution (LLSR) is a challenging task due to the coupled degradation of low resolution and poor illumination. To address this, we propose the Guided Texture…
U-Harmony: Enhancing Joint Training for Segmentation Models with Universal Harmonization
Weiwei Ma, Xiaobing Yu, Peijie Qiu +7
In clinical practice, medical segmentation datasets are often limited and heterogeneous, with variations in modalities, protocols, and anatomical targets across institutions. Exist…