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Variational Autoencoder for Image-Based Augmentation of Eye-Tracking Data
2021
Journal of Imaging
Over the past decade, deep learning has achieved unprecedented successes in a diversity of application domains, given large-scale datasets. However, particular domains, such as healthcare, inherently suffer from data paucity and imbalance. Moreover, datasets could be largely inaccessible due to privacy concerns, or lack of data-sharing incentives. Such challenges have attached significance to the application of generative modeling and data augmentation in that domain. In this context, this
doi:10.3390/jimaging7050083
pmid:34460679
pmcid:PMC8321343
fatcat:bihahevljrat5gaddcwgjk3tlq