Deep Learning Models Based on Image Classification: A Review
Kavi B. Obaid, Subhi R. M. Zeebaree & Omar M. Ahmed
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.
Keywords: Deep Learning, Image Classification, Machine Learning, Models.
|Title:||Deep Learning Models Based on Image Classification: A Review|
|Author:||Kavi B. Obaid, Subhi R. M. Zeebaree & Omar M. Ahmed|
|Journal Name:||International Journal of Science and Business|
|ISSN:||ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)|
|Date of Publication:||20/10/2020|
|Paper Type:||Research article|
Cite This Article:
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, 4(11), 75-81. doi: https://doi.org/10.5281/zenodo.4108433
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About Author (s)
Kavi B. Obaid, Computer Science Department, College of Science, University of Zakho, Iraq (e-mail: email@example.com).
Subhi R. M. Zeebaree, Duhok Polytechnic University, Iraq (e-mail: firstname.lastname@example.org).
Omar M. Ahmed, (Corresponding author),Information Technology Department, Zakho Technical Institute, Duhok Polytechnic University, Iraq (e-mail: email@example.com).