Digital Processing and Deep Learning Techniques: A review of the Literature

Authors

  • Kifaa Hadi Thanoon Northern Technical University
  • Abdulwahhb Fathee Shareef Northern Technical University
  • Omar A. Alsaif Northern Technical University

DOI:

https://doi.org/10.56286/ntujet.v1i3.223

Keywords:

Digital image processing, Deep Learning (DL), Segmentation, Classification, Feature extraction, Convolutional Neural Networks (CNN).

Abstract

This the first goal of digital image processing was to aid a human observer in intercepting certain events taking place through such images, yet we are more inclined to suppress the observer. We want to ask the computer to automatically analyze images in the same approach that a human observer might. Mathematical approaches are used to process images in image processing.Different approaches are done to the image in image processing to obtain a better image.The main goal of image enhancement is processing certain image so that the result is more appropriate for a specific application compared to original image. The first part of the presented study gives an overview regarding the approaches of digital image processing, while the second section introduces the concept of deep learning (DL) approaches and compares them.

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Additional Files

Published

2022-09-11

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Articles

How to Cite

[1]
“Digital Processing and Deep Learning Techniques: A review of the Literature”, NTU-JET, vol. 1, no. 3, Sep. 2022, doi: 10.56286/ntujet.v1i3.223.

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