Unsupervised feature learning-based encoder and adversarial networks

Unsupervised feature learning-based encoder and adversarial networks

Abstract In this paper, we propose a novel deep learning-based feature learning architecture for object classification. Conventionally, deep learning methods are trained with supervised learning for object classification. But, this would require large amount of training data. Currently there are inc...

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Bibliographic Details
Main Authors: Endang Suryawati, Hilman F. Pardede, Vicky Zilvan, Ade Ramdan, Dikdik Krisnandi, Ana Heryana, R. Sandra Yuwana, R. Budiarianto Suryo Kusumo, Andria Arisal, Ahmad Afif Supianto
Format: Article
Language:English
Published: SpringerOpen 2021-09-01
Series:Journal of Big Data
Subjects:
Generative adversarial network
Unsupervised feature learning
Autoencoder
Convolutional neural networks
Online Access:https://doi.org/10.1186/s40537-021-00508-9

Internet

https://doi.org/10.1186/s40537-021-00508-9

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