Self supervised contrastive learning for digital histopathology
Unsupervised learning has been a long-standing goal of machine learning and is especially important for medical image analysis, where the learning can compensate for the scarcity of labeled datasets. A promising subclass of unsupervised learning is self-supervised learning, which aims to learn salie...
Guardado en:
Autores principales: | Ozan Ciga, Tony Xu, Anne Louise Martel |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://doaj.org/article/7734613d34b04ca98d851e4bd8392267 |
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