Representation learning via a semi-supervised stacked distance autoencoder for image classification

Image classification is an important application of deep learning. In a typical classification task, the classification accuracy is strongly related to the features that are extracted via deep learning methods. An autoencoder is a special type of neural network, often used for dimensionality reducti...

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Bibliographic Details
Published in:	Frontiers of information technology & electronic engineering Vol. 21; no. 7; pp. 1005 - 1018
Main Authors:	Hou, Liang, Luo, Xiao-yi, Wang, Zi-yang, Liang, Jun
Format:	Journal Article
Language:	English
Published:	Hangzhou Zhejiang University Press 01.07.2020 Springer Nature B.V College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
Subjects:	Classification Communications Engineering Computer Hardware Computer Science Computer Systems Organization and Communication Networks Datasets Deep learning Electrical Engineering Electronics and Microelectronics Feature extraction Image classification Instrumentation Machine learning Networks Neural networks Object recognition Traffic signs TP391.9 Neural network Autoencoder Semi-supervised learning Image classification
ISSN:	2095-9184, 2095-9230
Online Access:	Get full text
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