3 citations · 3 across the 18 of their papers we have counts for
7 papers · 2 filters
EEMS: Edge-Prompt Enhanced Medical Image Segmentation Based on Learnable Gating Mechanism
Han Xia, Quanjun Li, Qian Li +5
Medical image segmentation is vital for diagnosis, treatment planning, and disease monitoring but is challenged by complex factors like ambiguous edges and background noise. We int…
DTEA: Dynamic Topology Weaving and Instability-Driven Entropic Attenuation for Medical Image Segmentation
Weixuan Li, Quanjun Li, Guang Yu +5
In medical image segmentation, skip connections are used to merge global context and reduce the semantic gap between encoder and decoder. Current methods often struggle with limite…
PC-UNet: An Enforcing Poisson Statistics U-Net for Positron Emission Tomography Denoising
Yang Shi, Jingchao Wang, Liangsi Lu +9
Positron Emission Tomography (PET) is crucial in medicine, but its clinical use is limited due to high signal-to-noise ratio doses increasing radiation exposure. Lowering doses inc…
SFormer: SNR-guided Transformer for Underwater Image Enhancement from the Frequency Domain
Xin Tian, Yingtie Lei, Xiujun Zhang +3
Recent learning-based underwater image enhancement (UIE) methods have advanced by incorporating physical priors into deep neural networks, particularly using the signal-to-noise ra…
CMAMRNet: A Contextual Mask-Aware Network Enhancing Mural Restoration Through Comprehensive Mask Guidance
Yingtie Lei, Fanghai Yi, Yihang Dong +5
Murals, as invaluable cultural artifacts, face continuous deterioration from environmental factors and human activities. Digital restoration of murals faces unique challenges due t…
MCA-LLaVA: Manhattan Causal Attention for Reducing Hallucination in Large Vision-Language Models
Qiyan Zhao, Xiaofeng Zhang, Yiheng Li +7
Hallucinations pose a significant challenge in Large Vision Language Models (LVLMs), with misalignment between multimodal features identified as a key contributing factor. This pap…
MAC-Lookup: Multi-Axis Conditional Lookup Model for Underwater Image Enhancement
Fanghai Yi, Zehong Zheng, Zexiao Liang +4
Enhancing underwater images is crucial for exploration. These images face visibility and color issues due to light changes, water turbidity, and bubbles. Traditional prior-based me…