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Found 7 papers, 7 papers with code
Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction
Despite advantages of multimodal learning for cancer survival prediction, massive redundancy in multimodal data prevents it from extracting discriminative and compact information: (1) An extensive amount of intra-modal task-unrelated information blurs discriminability, especially for gigapixel whole slide images (WSIs) with many patches in pathology and thousands of pathways in genomic data, leading to an ``intra-modal redundancy" issue.
Zero-Shot Image Harmonization with Generative Model Prior
Initially, we employ a pretrained vision-language model (VLM) to generate descriptions for the composite image.
ECL: Class-Enhancement Contrastive Learning for Long-tailed Skin Lesion Classification
In this paper, we propose class-Enhancement Contrastive Learning (ECL), which enriches the information of minority classes and treats different classes equally.
Diffusion Models for Imperceptible and Transferable Adversarial Attack
Many existing adversarial attacks generate $L_p$-norm perturbations on image RGB space.
Dense Pixel-to-Pixel Harmonization via Continuous Image Representation
High-resolution (HR) image harmonization is of great significance in real-world applications such as image synthesis and image editing.
Ranked #8 on
Image Harmonization
on iHarmony4
TFormer: A throughout fusion transformer for multi-modal skin lesion diagnosis
Multi-modal skin lesion diagnosis (MSLD) has achieved remarkable success by modern computer-aided diagnosis (CAD) technology based on deep convolutions.
A Rotation Meanout Network with Invariance for Dermoscopy Image Classification and Retrieval
As such they have made great improvements in many tasks of dermoscopy images.
