Artificial Neural Network algorithm for image Compression and Edge Detection

Authors

  • Asma Abdulelah Abdulrahman

Keywords:

Artificial Neural Network (ANN), Fully Connected Network (FC), Convolution Neural Network (CNN)

Abstract

In recent years, detection of things measured in the PASCAL VOC dataset has stabilized. Low-level image features and high-level context. There are many ways to perform complex grouping systems that combine image features in this work. An algorithm has been proposed to reveal the edge of the image in the proposed way Fully Connected Network (FC) by Convolution Neural Network (CNN) in short time using CNN method to reduce the space occupied by the original information of the image. To highlight the role of Artificial Neural Network (ANN) in the field of images to detect the edges using modern techniques in many areas of science, engineering and medicine, where the images of the cancerous cells algorithm that was created in this paper are revealed showing the importance of Artificial Neural Network (ANN) and Fully Connected Network (FC) by Convolution Neural Network (CNN) to detect cancer cells and tumors.

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Published

2021-03-30

How to Cite

Asma Abdulelah Abdulrahman, A. (2021). Artificial Neural Network algorithm for image Compression and Edge Detection . Journal of Kufa for Mathematics and Computer, 8(1), 33–38. Retrieved from https://journal.uokufa.edu.iq/index.php/jkmc/article/view/3196