Autoencoder and Its Various Variants

The concept of autoencoder was originally proposed by LeCun in 1987, early works on autoencoder were used for dimensionality reduction or feature learning. Recently, with the popularity of deep learning research, autoencoder has been brought to the forefront of generative modeling. Many variants of...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics s. 415 - 419
Hlavní autoři: Zhai, Junhai, Zhang, Sufang, Chen, Junfen, He, Qiang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.10.2018
Témata:
autoencoder
decoder
deep learning
feature learning
generative model
ISSN:2577-1655
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:The concept of autoencoder was originally proposed by LeCun in 1987, early works on autoencoder were used for dimensionality reduction or feature learning. Recently, with the popularity of deep learning research, autoencoder has been brought to the forefront of generative modeling. Many variants of autoencoder have been proposed by different researchers and have been successfully applied in many fields, such as computer vision, speech recognition and natural language processing. In this paper, we present a comprehensive survey on autoencoder and its various variants. Furthermore, we also present the lineage of the surveyed autoencoders. This paper can provide researchers engaged in related works with very valuable help.
ISSN:2577-1655
DOI:10.1109/SMC.2018.00080