Description
This paper is centered on the use of generative adversarial networks (GANs) to convert or generate RGB images from grayscale ones. The primary goal is to create sensible and colorful versions of a set of grayscale images by training a discriminator to recognize failed or generated images and training a generator to attempt to satisfy the discriminator. The network design is described in further detail below; however there are several potential issues that arise including the averaging of a color for certain images such that small details in an image are not assigned unique colors leading to a neutral blend. We attempt to mitigate this issue as much as possible.
Details
Title
- Using Neural Networks to Perform Colorwork on Images
Contributors
- Masud, Abdullah Bin (Co-author)
- Koleber, Keith (Co-author)
- Lobo, Ian (Co-author)
- Markabawi, Jah (Co-author)
- Yang, Yingzhen (Thesis director)
- Wang, Yancheng (Committee member)
- Computer Science and Engineering Program (Contributor, Contributor)
- Barrett, The Honors College (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2021-05
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