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

Abstract

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.