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cs.CV2026
DisMix: Order-Aware Mixup for Medical Imaging via Disentangling Ordinal and Non-Ordinal Features
Dileepa Pitawela, Gustavo Carneiro, Hsiang-Ting Chen
Image mixup is a widely adopted data augmentation strategy, yet it is ill-suited for ordinal classification tasks such as medical disease grading, where labels encode a progression…
cs.CV2026
Understanding Annotation Error Propagation and Learning an Adaptive Policy for Expert Intervention in Barrett's Video Segmentation
Lokesha Rasanjalee, Jin Lin Tan, Dileepa Pitawela +2
Accurate annotation of endoscopic videos is essential yet time-consuming, particularly for challenging datasets such as dysplasia in Barrett's esophagus, where the affected regions…
cs.CV2026
CLOC: Contrastive Learning for Ordinal Classification with Multi-Margin N-pair Loss
Dileepa Pitawela, Gustavo Carneiro, Hsiang-Ting Chen
In ordinal classification, misclassifying neighboring ranks is common, yet the consequences of these errors are not the same. For example, misclassifying benign tumor categories is…