Learning Approaches used by Different Applications to Achieve Deep Fake Technology

Authors

  • Ashish Maharjan Computer Engineer, COAC, Germany
  • Asish Shakya Kathmandu Model College, Bagbazar, Kathmandu, Nepal

DOI:

https://doi.org/10.3126/idjina.v2i1.55969

Keywords:

deepfake, machine learning, artificial, detection, verification

Abstract

Deepfake technology is an emerging field that has gained considerable attention in recent years. Deepfakes are synthetic media, including images, videos, and audio recordings, that are manipulated by advanced machine learning algorithms to produce convincing yet entirely artificial content.  This paper explores the various applications and the technologies used by them to achieve deep fake. The machine learning algorithms and the software are used by each  of them for proper execution of the technology. Further, we discuss the future prospects of the deepfake technology and explore future directions for research and development in this area, including the need for improved detection and verification techniques and increased education and awareness among the public.

Downloads

Download data is not yet available.
Abstract
48
pdf
69

Downloads

Published

2023-06-22

How to Cite

Maharjan, A., & Shakya, A. (2023). Learning Approaches used by Different Applications to Achieve Deep Fake Technology. Interdisciplinary Journal of Innovation in Nepalese Academia, 2(1), 96–101. https://doi.org/10.3126/idjina.v2i1.55969

Issue

Section

Part I: Management, Social & Computer Science