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Found 3 papers, 1 papers with code
CASED: Curriculum Adaptive Sampling for Extreme Data Imbalance
We introduce CASED, a novel curriculum sampling algorithm that facilitates the optimization of deep learning segmentation or detection models on data sets with extreme class imbalance.
Deep learning trends for focal brain pathology segmentation in MRI
In this chapter, we provide a survey of CNN methods applied to medical imaging with a focus on brain pathology segmentation.
HeMIS: Hetero-Modal Image Segmentation
We introduce a deep learning image segmentation framework that is extremely robust to missing imaging modalities.
Ranked #98 on
Semantic Segmentation
on NYU Depth v2
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