Variational autoencoder for image-based augmentation of eye-tracking data
M Elbattah, C Loughnane, JL Guérin, R Carette… - Journal of …, 2021 - mdpi.com
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 …
of application domains, given large-scale datasets. However, particular domains, such as …
Deep learning methods for the prediction of information display type using eye tracking sequences
Eye tracking data can help design effective user interfaces by showing how users visually
process information. In this study, three neural network models were developed and …
process information. In this study, three neural network models were developed and …
DPLRS: distributed population learning rate schedule
J Wei, X Zhang, Z Ji, Z Wei, J Li - Future Generation Computer Systems, 2022 - Elsevier
Deep neural network models perform very brightly in the field of artificial intelligence, but
their success is affected by hyperparameters, and the learning rate schedule is one of the …
their success is affected by hyperparameters, and the learning rate schedule is one of the …