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Found 3 papers, 2 papers with code
Meta-Learners for Few-Shot Weakly-Supervised Medical Image Segmentation
Most uses of Meta-Learning in visual recognition are very often applied to image classification, with a relative lack of works in other tasks {such} as segmentation and detection.
Weakly Supervised Few-Shot Segmentation Via Meta-Learning
Semantic segmentation is a classic computer vision task with multiple applications, which includes medical and remote sensing image analysis.
Learning to Segment Medical Images from Few-Shot Sparse Labels
In this paper, we propose a novel approach for few-shot semantic segmentation with sparse labeled images.
Few-Shot Semantic Segmentation
Medical Image Segmentation
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