A deep contractive autoencoder for solving multiclass classification problems

Contractive auto encoder (CAE) is on of the most robust variant of standard Auto Encoder (AE). The major drawback associated with the conventional CAE is its higher reconstruction error during encoding and decoding process of input features to the network. This drawback in the operational procedure...

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Veröffentlicht in:	Evolutionary intelligence Jg. 14; H. 4; S. 1619 - 1633
Hauptverfasser:	Aamir, Muhammad, Mohd Nawi, Nazri, Wahid, Fazli, Mahdin, Hairulnizam
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2021 Springer Nature B.V
Schlagworte:	Applications of Mathematics Artificial Intelligence Bioinformatics Classification Classifiers Coders Control Engineering Errors Feature extraction Mathematical and Computational Engineering Mechatronics Model testing Reconstruction Research Paper Robotics Statistical Physics and Dynamical Systems Deep auto encoder Contractive auto encoder Feature reduction MNIST variants Classification
ISSN:	1864-5909, 1864-5917
Online-Zugang:	Volltext
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