List of Deep Learning Models

  • Amir MosaviEmail author
  • Sina Ardabili
  • Annamária R. Várkonyi-Kóczy
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 101)


Deep learning (DL) algorithms have recently emerged from machine learning and soft computing techniques. Since then, several deep learning (DL) algorithms have been recently introduced to scientific communities and are applied in various application domains. Today the usage of DL has become essential due to their intelligence, efficient learning, accuracy and robustness in model building. However, in the scientific literature, a comprehensive list of DL algorithms has not been introduced yet. This paper provides a list of the most popular DL algorithms, along with their applications domains.


Deep learning Machine learning Convolutional neural networks (CNN) Recurrent neural networks (RNN) Denoising autoencoder (DAE) Deep belief networks (DBNs) Long short-term memory (LSTM) 



This publication has been supported by the Project: “Support of research and development activities of the J. Selye University in the field of Digital Slovakia and creative industry” of the Research & Innovation Operational Programme (ITMS code: NFP313010T504) co-funded by the European Regional Development Fund.


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institue of Automation, Kalman Kando Faculty of Electrical EngineeringObuda UniversityBudapestHungary
  2. 2.School of the Built EnvironmentOxford Brookes UniversityOxfordUK
  3. 3.Institute of Advanced Studies KoszegKoszegHungary
  4. 4.Department of Mathematics and InformaticsJ. Selye UniversityKomarnoSlovakia

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