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Found 4 papers, 3 papers with code
What Makes Transfer Learning Work For Medical Images: Feature Reuse & Other Factors
Transfer learning is a standard technique to transfer knowledge from one domain to another.
CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer
Interval and large invasive breast cancers, which are associated with worse prognosis than other cancers, are usually detected at a late stage due to false negative assessments of screening mammograms.
Should we Replace CNNs with Transformers for Medical Images?
Convolutional Neural Networks (CNNs) have reigned for a decade as the de facto approach to automated medical image diagnosis, pushing the state-of-the-art in classification, detection and segmentation tasks.
Full-Glow: Fully conditional Glow for more realistic image generation
Autonomous agents, such as driverless cars, require large amounts of labeled visual data for their training.
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