5 papers
Intrinsic Concept Extraction Based on Compositional Interpretability
Hanyu Shi, Hong Tao, Guoheng Huang +5
Unsupervised Concept Extraction aims to extract concepts from a single image; however, existing methods suffer from the inability to extract composable intrinsic concepts. To addre…
Generative AI Enables EEG Super-Resolution via Spatio-Temporal Adaptive Diffusion Learning
Shuqiang Wang, Tong Zhou, Yanyan Shen +3
Electroencephalogram (EEG) technology, particularly high-density EEG (HD EEG) devices, is widely used in fields such as neuroscience. HD EEG devices improve the spatial resolution…
AFFSegNet: Adaptive Feature Fusion Segmentation Network for Microtumors and Multi-Organ Segmentation
Fuchen Zheng, Xinyi Chen, Xuhang Chen +5
Medical image segmentation, a crucial task in computer vision, facilitates the automated delineation of anatomical structures and pathologies, supporting clinicians in diagnosis, t…
IMAN: An Adaptive Network for Robust NPC Mortality Prediction with Missing Modalities
Yejing Huo, Guoheng Huang, Lianglun Cheng +5
Accurate prediction of mortality in nasopharyngeal carcinoma (NPC), a complex malignancy particularly challenging in advanced stages, is crucial for optimizing treatment strategies…
TAGE: Trustworthy Attribute Group Editing for Stable Few-shot Image Generation
Ruicheng Zhang, Guoheng Huang, Yejing Huo +4
Generative Adversarial Networks (GANs) have emerged as a prominent research focus for image editing tasks, leveraging the powerful image generation capabilities of the GAN framewor…