IDEAS home Printed from https://ideas.repec.org/a/aif/journl/v4y2020i11p75-81.html
   My bibliography  Save this article

Deep Learning Models Based on Image Classification: A Review

Author

Listed:
  • Kavi B. Obaid

    (Computer Science Department, College of Science, University of Zakho, Iraq.)

  • Subhi R. M. Zeebaree

    (Duhok Polytechnic University, Iraq.)

  • Omar M. Ahmed

    (Information Technology Department, Zakho Technical Institute, Duhok Polytechnic University, Iraq)

Abstract

With the development of the big data age, deep learning developed to become having a more complex network structure and more powerful feature learning and feature expression abilities than traditional machine learning methods. The model trained by the deep learning algorithm has made remarkable achievements in many large-scale identification tasks in the field of computer vision since its introduction. This paper first introduces the deep learning, and then the latest model that has been used for image classification by deep learning are reviewed. Finally, all used deep learning models in the literature have been compared to each other in terms of accuracy for the two most challenging datasets CIFAR-10 and CIFAR-100.

Suggested Citation

  • Kavi B. Obaid & Subhi R. M. Zeebaree & Omar M. Ahmed, 2020. "Deep Learning Models Based on Image Classification: A Review," International Journal of Science and Business, IJSAB International, vol. 4(11), pages 75-81.
    • Handle: RePEc:aif:journl:v:4:y:2020:i:11:p:75-81
    as

    Download full text from publisher

    File URL: https://ijsab.com/wp-content/uploads/612.pdf
    Download Restriction: no
    File URL: https://ijsab.com/volume-4-issue-11/3290
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Ibrahim Shamal Abdulkhaleq & Subhi R. M. Zeebaree, 2021. "State of Art for Distributed Databases: Faster Data Access, processing, Growth Facilitation and Improved Communications," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 126-136.
    2. Zhwan M. Khalid & Subhi R.M Zeebaree, 2021. "Big Data Analysis for Data Visualization: A Review," International Journal of Science and Business, IJSAB International, vol. 5(2), pages 64-75.
    3. Mohammed J. Sadeeq & Subhi R. M. Zeebaree, 2021. "Semantic Search Engine Optimisation (SSEO) for Dynamic Websites: A Review," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 148-158.
    4. Kazheen Ismael Taher & Adnan Mohsin Abdulazeez, 2021. "Deep Learning Convolutional Neural Network for Speech Recognition: A Review," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 1-14.
    5. Chnar Mustafa Mohammed & Subhi R.M Zeebaree, 2021. "Sufficient Comparison Among Cloud Computing Services: IaaS, PaaS, and SaaS: A Review," International Journal of Science and Business, IJSAB International, vol. 5(2), pages 17-30.

    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:aif:journl:v:4:y:2020:i:11:p:75-81. 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: Farjana Rahman (email available below). General contact details of provider: .

    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.