On-the-Fly Improving Segment Anything for Medical Image Segmentation Using Auxiliary Online Learning
Abstract: The current variants of the Segment Anything Model (SAM), which include the original SAM and Medical SAM, still lack the capability to produce sufficiently accurate segmentation for medical ...
Brazil is home to some of the planet’s largest areas of tropical forest, but they are under intense pressure. The Atlantic Forest, on the country’s eastern coast, once covered 350 million acres, but ...
Abstract: Weakly-supervised learning methods have become increasingly attractive for medical image segmentation, but suffered from a high dependence on quantifying the pixel-wise affinities of ...
Abstract: Accurate tree crown delineation from very high-resolution UAV orthophotos in urban areas remains challenging due to landscape complexity and the scarcity of representative annotated data.
Abstract: In order to detect cavities on teeth, dentists analyse dental x-rays. Initially, dental cavities develop on the delicate surface of the teeth, known as enamel, and subsequently progress to ...
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