U_Net_Ni_WC_Optical_images
Published: 4 May 2022| Version 1 | DOI: 10.17632/2wmbc95xy9.1
Contributor:
Dylan RoseDescription
This data was used to train a U-Net convolutional neural network to semantically segment WC from Ni-WC optical microscopy images. The training and test datasets contain 194 and 37 512x512 pixel images and their corresponding ground truths, respectively.
Files
Institutions
University of Alberta
Categories
Computer Vision, Image Segmentation, Metal Matrix Composite, Light Microscopy