A Survey on Image Data Augmentation for Deep Learning

2019 article shorten2019augmentationsurvey ○ Not yet verified

Authors

Connor Shorten, Taghi M. Khoshgoftaar

Venue

Journal of Big Data

Abstract

Comprehensive survey of image data augmentation techniques for deep learning, covering geometric transformations, color space transforms, kernel filters, mixing images, random erasing, and neural style transfer approaches.

BibTeX

Local Entry

@article{shorten2019augmentationsurvey,
  title = {A Survey on Image Data Augmentation for Deep Learning},
  author = {Connor Shorten and Taghi M. Khoshgoftaar},
  year = {2019},
  journal = {Journal of Big Data},
  url = {https://link.springer.com/article/10.1186/s40537-019-0197-0},
  abstract = {Comprehensive survey of image data augmentation techniques for deep learning, covering geometric transformations, color space transforms, kernel filters, mixing images, random erasing, and neural style transfer approaches.}
}

From OPENALEX

@article{shorten2019augmentationsurvey,
  title = {A survey on Image Data Augmentation for Deep Learning},
  author = {Connor Shorten and Taghi M. Khoshgoftaar},
  year = {2019},
  journal = {Journal Of Big Data},
  doi = {10.1186/s40537-019-0197-0}
}