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TP-DRSeg: improving diabetic retinopathy lesion segmentation with explicit text-prompts assisted SAM
Recent advances in large foundation models, such as the Segment Anything Model (SAM),
have demonstrated considerable promise across various tasks. Despite their progress …
have demonstrated considerable promise across various tasks. Despite their progress …
Generalizing to unseen domains in diabetic retinopathy with disentangled representations
Diabetic Retinopathy (DR), induced by diabetes, poses a significant risk of visual
impairment. Accurate and effective grading of DR aids in the treatment of this condition. Yet …
impairment. Accurate and effective grading of DR aids in the treatment of this condition. Yet …
Diffusion model driven test-time image adaptation for robust skin lesion classification
Deep learning-based diagnostic systems have demonstrated potential in skin disease
diagnosis. However, their performance can easily degrade on test domains due to …
diagnosis. However, their performance can easily degrade on test domains due to …
LMPT: prompt tuning with class-specific embedding loss for long-tailed multi-label visual recognition
Long-tailed multi-label visual recognition (LTML) task is a highly challenging task due to the
label co-occurrence and imbalanced data distribution. In this work, we propose a unified …
label co-occurrence and imbalanced data distribution. In this work, we propose a unified …
Hierarchical fine-grained visual classification leveraging consistent hierarchical knowledge
Y Liu, L Yang, Y Wang - Joint European Conference on Machine Learning …, 2024 - Springer
Hierarchical fine-grained visual classification assigns multi-granularity labels to each object,
forming a tree hierarchy. However, how to minimize the impact of coarse-grained …
forming a tree hierarchy. However, how to minimize the impact of coarse-grained …