An Introduction to Deep Learing in Image Recognition（2）: 　Configuration of GPU Environments and Application to Image Segmentation

DOI
  • HARA Takeshi
    Gifu University Center for Healthcare Information Technology (C-HiT), Tokai National Higher Education and ResearchSystem
  • ODA Masahiro
    Nagoya University

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Other Title
  • 深層学習による画像認識入門（2） GPU 環境構築と画像の領域分割

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Abstract

<p>In order to set up a practical experiment and research environment for deep learning, it is necessary to build an computing environment using GPU. This is because the calculation speed is several tens of times faster than the calculation using only the CPU. In this course, we will explain how to build a GPU environment and clarify how much the calculation time changes, using image segmentation as an example. At the same time, the method of image segmentation using U-Net model and the construction of the label data are also mentioned.</p>

Journal

  • Medical Imaging Technology

    Medical Imaging Technology 39 (3), 124-130, 2021-05-25

    The Japanese Society of Medical Imaging Technology

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