Fully unsupervised deep mode of action learning for phenotyping high-content cellular images
Motivation: The identification and discovery of phenotypes from high content screening images is a challenging task. Earlier works use image analysis pipelines to extract biological features, supervised training methods or generate features with neural networks pretrained on non-cellular images. We...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Oxford University Press
2021
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| Online Access: | View Fulltext in Publisher |