conference paper

Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction

Jonathan Masci^{a b}, Ueli Meier^{a b}, Dan Claudiu Ciresan^{a b}, Jürgen Schmidhuber^{a b}

^aIstituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Lugano, Switzerland
^bIstituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), Lugano, Switzerland

Lecture notes in computer science Springer Science+Business Media2011-01-01 2,169 citations35 references

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TL;DRA novel convolutional auto-encoder (CAE) for unsupervised feature learning that initializing a CNN with filters of a trained CAE stack yields superior performance on a digit and an object recognition benchmark. (Semantic Scholar)

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Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction

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