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Home / Publications / ePress Series / A Comprehensive Review of Deep Learning Algorithms

A Comprehensive Review of Deep Learning Algorithms


Deep learning algorithms are a subset of machine learning algorithms that aim to explore several levels of the distributed representations from the input data. Recently, many deep learning algorithms have been proposed to solve traditional artificial intelligence problems. In this review paper, some of the up-to-date algorithms of this topic in the field of computer vision and image processing are reviewed. Following this, a brief overview of several different deep learning methods and their recent developments are discussed.

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Varastehpour, S., Sharifzadeh, H., Ardekani, I. (2021). A Comprehensive Review of Deep Learning Algorithms. Unitec ePress Occasional and Discussion Papers Series (2021: 4).

https://doi.org/10.34074/ocds.092

About this series:

Unitec ePress periodically publishes occasional and discussion papers that discuss current and ongoing research authored by members of staff and their research associates. All papers are blind reviewed. For more papers in this series please visit: www.unitec.ac.nz/epress/index.php/category/publications/epressseries/discussion-and-occasionalpapers

  • Authors: Dr Soheil Varastehpour, Dr Hamid Sharifzadeh, Dr Iman Ardekani
  • Date of publication: 26.11.2021
  • ISSN: 2324-3635

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