U-Net Convolutional Neural Networks for Image Segmentation: Application to SEM Images of Graphene

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Aagam Shah, University of Illinois at Urbana-Champaign

This video is part of NCN's Hands-on Data Science and Machine Learning Training Series which can be found at:

In digital image processing and computer vision, image segmentation refers to the process of partitioning a digital image into multiple segments or related sets of pixels. This tutorial introduces you to U-Net, a popular convolutional neural network commonly developed for image segmentation in biomedicine. Using an assembled data set, you will learn how to create and train a U-Net neural network, and apply it to segment scanning electron microscopy images of graphene on a substrate.

This talk and additional downloads can be found on at:
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