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Machine Learning and Imaging Lecture 10 Part 3: Ingredients of a Convolutional Neural Network

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Duke Computational Optics Lab

In this lecture, Dr. Horstmeyer finishes describing the basic components of a convolutional neural network (CNN). This includes optimization methods to improve CNN performance, such as the use of batch normalization, dropout, data augmentation, and methods to initialize network weights. Additional resources are available at deepimaging.github.io

posted by longimanez6