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Found 4 papers, 1 papers with code
EGDCL: An Adaptive Curriculum Learning Framework for Unbiased Glaucoma Diagnosis
Today's computer-aided diagnosis (CAD) model is still far from the clinical practice of glaucoma detection, mainly due to the training bias originating from 1) the normal-abnormal class imbalance and 2) the rare but significant hard samples in fundus images.
Improving Knowledge Distillation via Category Structure
Intra-category structure penalizes the structured relations in samples from the same category and inter-category structure focuses on cross-category relations at a category level.
A Refined Equilibrium Generative Adversarial Network for Retinal Vessel Segmentation
In this work, we present an end-to-end synthetic neural network, containing a symmetric equilibrium generative adversarial network (SEGAN), multi-scale features refine blocks (MSFRB), and attention mechanism (AM) to enhance the performance on vessel segmentation.
Dual-attention Focused Module for Weakly Supervised Object Localization
In each branch, the input feature map is deduced into an enhancement map and a mask map, thereby highlighting the most discriminative parts or hiding them.
