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Found 6 papers, 4 papers with code
Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation
Single domain generalization aims to address the challenge of out-of-distribution generalization problem with only one source domain available.
D-CoRP: Differentiable Connectivity Refinement for Functional Brain Networks
Existing models for brain networks typically primarily focus on brain regions or overlook the complexity of brain connectivities.
Weakly supervised segmentation with point annotations for histopathology images via contrast-based variational model
Image segmentation is a fundamental task in the field of imaging and vision.
DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classification
Multiple instance learning (MIL) has been increasingly used in the classification of histopathology whole slide images (WSIs).
BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation
Our model is well-suited to obtain global semantic region information while also accommodates local spatial boundary characteristics simultaneously.
Spatial Uncertainty-Aware Semi-Supervised Crowd Counting
Semi-supervised approaches for crowd counting attract attention, as the fully supervised paradigm is expensive and laborious due to its request for a large number of images of dense crowd scenarios and their annotations.
