Web: http://arxiv.org/abs/2201.11333

Jan. 28, 2022, 2:11 a.m. | Luzhe Huang, Xilin Yang, Tairan Liu, Aydogan Ozcan

cs.LG updates on arXiv.org arxiv.org

Deep learning-based methods in computational microscopy have been shown to be
powerful but in general face some challenges due to limited generalization to
new types of samples and requirements for large and diverse training data.
Here, we demonstrate a few-shot transfer learning method that helps a
holographic image reconstruction deep neural network rapidly generalize to new
types of samples using small datasets. We pre-trained a convolutional recurrent
neural network on a large dataset with diverse types of samples, which serves …

arxiv learning network neural neural network recurrent neural network transfer learning

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