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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
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    Citations

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    Cited by:

    1. 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.
    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. 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.
    4. 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.
    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.

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