Abstract: Few-shot segmentation is an important approach for mitigating issues related to data annotation and model generalization. However, when applied to medical images, two challenges arise.
Abstract: Few-Shot Object Detection (FSOD) aims to detect the objects of novel classes using only a few manually annotated samples. With the few novel class samples, learning the inter-class ...
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