A better way to learn features

15 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Deep Learning: Methods and Applications (2014, background): “Examples are transforming autoencoders [160], predictive sparse coders and their stacked version, and de-noising autoencoders and their stacked versions [376].”
Scene classification based on single-layer SAE and SVM (2015, methodology): “As a representation learning model, single-layer SAE can learn good representations from source data and make it easier to extract sufficient and appropriate information when building classifier (Hinton, 2011; Krizhevsky et al., 2012).”
A Review of Deep Learning with Special Emphasis on Architectures, Applications and Recent Trends (2019, methodology): “Transforming autoencoders [95] proposed as a autoencoder with transformation invariant property.”