Published June 23, 2024 | Version v1

ARTIFICIAL INTELLIGENCE TECHNIQUES IN MULTIMEDIA

  • 1. Ajloun National University, Information Technology College, Ajloun, Jordan

Description

Artificial Intelligence (AI) has emerged as a transformative force in the field of multimedia, revolutionizing content creation, analysis, and delivery across various industries. This paper explores the integration of AI techniques in multimedia applications and its profound implications for enhancing creativity and efficiency. Drawing upon existing literature and case studies, the paper examines the impact of AI-powered multimedia technologies on industries such as entertainment, advertising, education, and healthcare. Furthermore, the paper identifies key challenges and opportunities associated with the integration of AI and multimedia, including technical limitations, ethical considerations, and societal implications.

Files

462-467 Amer A new MJST.pdf

Files (619.7 kB)

Name Size Download all
md5:c94d76eac1bb4cddea995f0a657f2ca2
619.7 kB Preview Download

Additional details

References

  • 1. Deineko, Zh., Kraievska, N., & Lyashenko, V. (2022). QR Code as an Element of Educational Activity. International Journal of Academic Information Systems Research (IJAISR), 6(4), 26-31.
  • 2. Sotnik, S., Mustafa, S. K., Ahmad, M. A., Lyashenko, V., & Zeleniy, O. (2020). Some features of route planning as the basis in a mobile robot. International Journal of Emerging Trends in Engineering Research, 8(5), 2074-2079.
  • 3. Lyubchenko, V., & et al.. (2016). Digital image processing techniques for detection and diagnosis of fish diseases. International Journal of Advanced Research in Computer Science and Software Engineering, 6(7), 79-83.
  • 4. Al-Sherrawi, M. H., Lyashenko, V., Edaan, E. M., & Sotnik, S. (2018). Corrosion as a source of destruction in construction. International Journal of Civil Engineering and Technology, 9(5), 306-314.
  • 5. Lyashenko, V. V., Deineko, Z. V., & Ahmad, M. A. Properties of wavelet coefficients of self-similar time series. In other words, 9, 16.
  • 6. Baranova, V., Zeleniy, O., Deineko, Z., & Lyashenko, V. (2019, October). Stochastic Frontier Analysis and Wavelet Ideology in the Study of Emergence of Threats in the Financial Markets. In 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T) (pp. 341-344). IEEE.
  • 7. Dobrovolskaya, I., & Lyashenko, V. (2013). Interrelations of banking sectors of European economies as reflected in separate indicators of the dynamics of their cash flows influencing the formation of the resource potential of banks. European Applied Sciences, 1-2, 114-118.
  • 8. Kots, G. P., & Lyashenko, V. (2012). Banking sectors of the economies of European countries in the representation of statistical interrelation between indices that characterize their development. European Applied Sciences, 1, 461-465.
  • 9. Kuzemin, A., & Lyashenko, V. (2009). Methods of comparative analysis of banks functioning: classic and new approaches. Information Theories & Applications, 16(4), 384-396.
  • 10. Mustafa, S. K., Yevsieiev, V., Nevliudov, I., & Lyashenko, V. (2022). HMI Development Automation with GUI Elements for Object-Oriented Programming Languages Implementation. SSRG International Journal of Engineering Trends and Technology, 70(1), 139-145.