The filling-in function of the Bayesian AutoEncoder Network

Kaneharu Nishino; Mary Inaba

doi:10.1117/12.2280931

19 June 2017 The filling-in function of the Bayesian AutoEncoder Network

Kaneharu Nishino, Mary Inaba

Proceedings Volume 10443, Second International Workshop on Pattern Recognition; 104431E (2017) https://doi.org/10.1117/12.2280931
Event: Second International Workshop on Pattern Recognition, 2017, Singapore, Singapore

Abstract

We developed the Bayesian AutoEncoder (BAE) to construct a multi-layer restricted Bayesian Network by extracting features from a training dataset. Networks constructed using BAE have hidden variables that represent features of the data and can execute inferences for each feature. In this paper, we show that a network constructed by BAE can not only recognize features but can also fill in lacking data. We performed experiments and confirmed this filling-in ability.

Citation Download Citation

Kaneharu Nishino and Mary Inaba "The filling-in function of the Bayesian AutoEncoder Network", Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104431E (19 June 2017); https://doi.org/10.1117/12.2280931

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