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Found 3 papers, 1 papers with code
Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification
To address this challenge, we propose a medical-knowledge-guided one-class classification approach that leverages domain-specific knowledge of classification tasks to boost the model's performance.
Constrained Deep One-Class Feature Learning For Classifying Imbalanced Medical Images
These methods mainly focus on capturing either compact or descriptive features, where the information of the samples of a given one class is not sufficiently utilized.
Super-Resolution Domain Adaptation Networks for Semantic Segmentation via Pixel and Output Level Aligning
SRDA-Net can simultaneously achieve the super-resolution task and the domain adaptation task, thus satisfying the requirement of semantic segmentation for remote sensing images which usually involve various resolution images.
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