Constellation loss: Improving the efficiency of deep metric learning loss functions for the optimal embedding of histopathological images
Background: Deep learning diagnostic algorithms are proving comparable results with human experts in a wide variety of tasks, and they still require a huge amount of well-annotated data for training, which is often non affordable. Metric learning techniques have allowed a reduction in the required a...
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| Main Authors: | , |
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| Format: | Book |
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Elsevier,
2020-01-01T00:00:00Z.
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Internet
Connect to this object online.3rd Floor Main Library
| Call Number: |
A1234.567 |
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| Copy 1 | Available |