πŸ“š Vol. 1, No. 2 πŸ“… 2021 πŸ“„ Pages: 14 - 19 πŸ”— DOI: 10.52688/ASP53225

Grayscale image colorization using deep learning approach

✍️ Authors

Salwa Mohammed Nejrs Corresponding

πŸ“– Abstract

In today’s life, images become vital for various applications such as pattern recognition, security system, face recognition, remote sensing, etc. Due to the popularity of image processing applications, new fields begin to establish using the technology of image processing such as image colorization. In this paper, development of accurate convolutional neural network (CNN) based image colorization technique is performed. The performance of the said CNN to be optimized by optimizing each layer of the classifier. Performance of proposed classifier have been found equal to 95.91 Percent.
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πŸ”‘ Keywords

CNN Colorization RBG Bands Normalization Pixel Neural network.

πŸ“‹ Publication Information

Volume
1
Issue
2
Year
2021
Page Range
14 - 19
DOI
10.52688/ASP53225
Publication Date
2021.07.19

πŸ›οΈ Author Affiliation

Department of Physics, College of Science, University of Misan, Misan, Iraq

πŸ“ How to Cite this Article

Salwa Mohammed Nejrs . (2021). Grayscale image colorization using deep learning approach. Journal of Positive Sciences (JPS), 1(2), 14 - 19. https://doi.org/10.52688/259jps/ASP53225