To make full use of the representations of all layers, this paper proposes a feature ensemble learning method based on sparse autoencoders for image ...

Y. Lu, L. Zhang, B. Wang and J. Yang proposed feature ensemble learning based on Sparse Autoencoders for image classification to improve performance [24] .

This paper proposes a feature ensemble learning method based on sparse autoencoders for image classification that trains three softmax classifiers by using ...

2014 International Joint Conference on Neural Networks (IJCNN). July 6-11, 2014, Beijing, China. 978-1-4799-1484-5/14/$31.00 ©2014 IEEE.

For this problem, we proposed a feature ensemble learning method based on sparse autoencoders. The dataset for this purpose was obtained from UCI, an online ...

This paper proposes a feature ensemble learning method based on sparse autoencoders for image classification that trains three softmax classifiers by using ...

Jun 13, 2019 · Boosting sparsity-induced autoencoder: A novel sparse feature ensemble learning for image classification. Rui Shi, Jian Ji https://orcid.org ...

proposed a modified model using feature ensemble learning based on Sparse Autoencoders for image classification. Unlike SSAE-SM model, this model makes use ...

This paper proposes an embedded stacked group sparse autoencoder (ESGSAE) for more effective feature learning.

boost the autoencoders performance, an ensemble sparse feature learning algorithm based on SparsityAE is pro- posed, named Boosting sparsity-induced autoencoder.