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Testing the Segment Anything Model on radiology data
May 17, 2024, 4:43 a.m. | Jos\'e Guilherme de Almeida, Nuno M. Rodrigues, Sara Silva, Nickolas Papanikolaou
cs.LG updates on arXiv.org arxiv.org
Abstract: Deep learning models trained with large amounts of data have become a recent and effective approach to predictive problem solving -- these have become known as "foundation models" as they can be used as fundamental tools for other applications. While the paramount examples of image classification (earlier) and large language models (more recently) led the way, the Segment Anything Model (SAM) was recently proposed and stands as the first foundation model for image segmentation, trained …
abstract applications arxiv become classification cs.cv cs.lg data deep learning eess.iv examples foundation fundamental image predictive radiology replace segment segment anything segment anything model testing tools type while
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