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Reinforcing Medical Image Classifier to Improve Generalization on Small Datasets
[article]
2019
arXiv
pre-print
With the advents of deep learning, improved image classification with complex discriminative models has been made possible. However, such deep models with increased complexity require a huge set of labeled samples to generalize the training. Such classification models can easily overfit when applied for medical images because of limited training data, which is a common problem in the field of medical image analysis. This paper proposes and investigates a reinforced classifier for improving the
arXiv:1909.05630v2
fatcat:rzbsgytedjfkvc267dyrdrlz3y