Nonredundant sparse feature extraction using autoencoders with receptive fields clustering-Reference-Cited by-同舟云学术

Nonredundant sparse feature extraction using autoencoders with receptive fields clustering

Author:

Ayinde Babajide O.^ORCID,Zurada Jacek M.^ORCID

Funder

National Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference37 articles.

1. Visualizing and understanding nonnegativity constrained sparse autoencoder in deep learning;Ayinde,2016

2. Clustering of receptive fields in autoencoders;Ayinde,2016

3. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection;Belhumeur;IEEE Transactions on Pattern Analysis and Machine Intelligence,1997

4. Learning deep architectures for ai;Bengio;Foundations and trends® in Machine Learning,2009

5. Representation learning: A review and new perspectives;Bengio;IEEE Transactions on Pattern Analysis and Machine Intelligence,2013

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