Enhancement of Image Processing based on Deep Learning Backpropagation Approach

Authors

  • S.V.S. Ganga Devi Professor & Head, Department of CSE (Cyber Security), Madanapalle Institute of Technology & Science, Madanapalle
  • K. Gunasekaran Associate Professor, Department of Data Science, Sri Indu College of Engineering and Technology Hyderabad - 501510
  • M. Rajaram Narayanan Professor, Department of Mechanical Engineering, Dr.MGR Deemed University
  • A. Kanchana Assistant professor, Department of CSE, Panimalar Engineering College
  • G. Nalini Priya Professor, Department of Information Technology, Saveetha Engineering College, Chennai

Keywords:

Deep Learning, Back propagation neural network, Image processing

Abstract

By understanding the parameters and weights generated from the picture itself, utilizing a single deep learning (DL) technique, such as neural network backpropagation, enhances encryption achievements. Furthermore, inconsistency plays a major part in the encryption of photographs, particularly because smart learning techniques are utilized. The initial objective of any encryption technique is to yield a more complex encrypted picture that would be challenging or hard to decrypt regardless of the suggested key. In this paper, a flexible technique that allows picture encryption via deep learning backpropagation is proposed. This method is being implemented in Industry 5.0 to conveniently encrypt photos. Along with electrical, tangible, and information security, there are a ton of businesses relevant to image computing. These two phrases are derived from data security, specifically image privacy. Encrypting photographs successfully preserves quality and yields frenzied, good-looking pictures. The results of the experiments indicate that the backpropagation technique outperformed all other algorithms.

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References

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Published

27.12.2023

How to Cite

Ganga Devi, S. ., Gunasekaran, K. ., Narayanan, M. R. ., Kanchana, A. ., & Nalini Priya, G. . (2023). Enhancement of Image Processing based on Deep Learning Backpropagation Approach. International Journal of Intelligent Systems and Applications in Engineering, 12(9s), 32–38. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/4198

Issue

Vol. 12 No. 9s (2024)

Section

Research Article

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