IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/5548884.html
   My bibliography  Save this article

The Understanding of Deep Learning: A Comprehensive Review

Author

Listed:
  • Ranjan Kumar Mishra
  • G. Y. Sandesh Reddy
  • Himanshu Pathak

Abstract

Deep learning is a computer-based modeling approach, which is made up of many processing layers that are used to understand the representation of data with several levels of abstraction. This review paper presents the state of the art in deep learning to highlight the major challenges and contributions in computer vision. This work mainly gives an overview of the current understanding of deep learning and their approaches in solving traditional artificial intelligence problems. These computational models enhanced its application in object detection, visual object recognition, speech recognition, face recognition, vision for driverless cars, virtual assistants, and many other fields such as genomics and drug discovery. Finally, this paper also showcases the current developments and challenges in training deep neural network.

Suggested Citation

  • Ranjan Kumar Mishra & G. Y. Sandesh Reddy & Himanshu Pathak, 2021. "The Understanding of Deep Learning: A Comprehensive Review," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-15, April.
    • Handle: RePEc:hin:jnlmpe:5548884
    DOI: 10.1155/2021/5548884
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2021/5548884.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2021/5548884.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/5548884?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luís Rita & Miguel Peliteiro & Tudor-Codrin Bostan & Tiago Tamagusko & Adelino Ferreira, 2023. "Using Deep Learning and Google Street View Imagery to Assess and Improve Cyclist Safety in London," Sustainability, MDPI, vol. 15(13), pages 1-26, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:5548884. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.