Autoencoder Neural Networks

Autoencoder Neural Networks

Deep neural networks have had huge success in recent years. However training them efficiently is still a research area. In this project we investigated a type of neural network, autoencoder, and its variations. Autoencoder is an ANN that tries to reconstruct its input as output. While doing this, it learns features of data as a byproduct. It is also used as a pre-training tool for deep neural networks.

Project Poster: 

Project Members: 

Alper Ahmetoğlu

Project Advisor: 

Ethem Alpaydın

Project Status: 

Project Year: 

2017
  • Spring

Bize Ulaşın

Bilgisayar Mühendisliği Bölümü, Boğaziçi Üniversitesi,
34342 Bebek, İstanbul, Türkiye

  • Telefon: +90 212 359 45 23/24
  • Faks: +90 212 2872461
 

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