Advancements in Digital Image Processing Techniques for Assessing and Enhancing Image Quality

Authors

  • Dr Cyril Mathew O, Dr Balusamy R, Dr Nalini P, Dr Sivakumar C

Keywords:

Machine learning, neural network, accuracy, artificial intelligence, computations

Abstract

We live in the age of artificial intelligence, a branch of computer science that allows for the creation of intelligent machines that perform tasks similar to those performed by humans.A.I. is used in a variety of ways, including virtual personal assistants, robotics, search engines, and machine learning. Computer learning is a branch of artificial intelligence that has evolved the traditional way of computation into a self-learning machine.

References

A. Bashar, “Survey on evolving deep learning neural network architectures,” J. Artif. Intell., vol. 1, no. 2, pp. 73–82, 2019.

X. Qi, Y. Tang, M. A. M. Ali, H. Huang, and Y. Tian, “Applying neural-network-based machine learning to additive manufacturing: current applications, challenges, and future perspectives,” Engineering, vol. 5, no. 4, pp. 721–729, 2019.

K. T. Schütt, P. Kessel, M. Gastegger, K. A. Nicoli, A. Tkatchenko, and K. R. Müller, “Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions,” Nat. Commun., vol. 10, no. 1, pp. 1–10, 2019.

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Published

2024-02-13

How to Cite

Dr Cyril Mathew O, Dr Balusamy R, Dr Nalini P, Dr Sivakumar C. (2024). Advancements in Digital Image Processing Techniques for Assessing and Enhancing Image Quality. Journal of Computational Analysis and Applications (JoCAAA), 33(2), 1197–1206. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2217

Issue

Section

Articles