Earticle

초록

영어

A specific area of research in artificial intelligence, known as deep learning (DL) has turned into a strong source for the solutions of complicated issues in computer vision and many more. A real application of that is real and fake faces detection. Detection of is real and fake faces became increasingly important these days with increasing deepfake technology. Fake images pose great dangers to information security, trustworthiness in multimedia content, and even to society's stability. In his proposal the design of a deep learning-based model in VGG-16 architecture to make high accuracy and reliability distinctions between real and fake faces. The performance of the proposed model was evaluated by a number of metrics, including accuracy, specificity, recall, precision, and misclassification rate. The results showed that the model obtained an excellent accuracy of 99.61% with a very low misclassification rate of 0.39%. It obtained perfect specificity of 99.15%, which means all fake faces were identified correctly, and a precision value of 99.29%, ensuring that all faces classified as real were indeed real. The recall of the model was high, at 100%, meaning nearly all real faces were correctly identified. The obtained results are the proof of how effective DL and, in this case, using a pre-trained model like VGG-16, is at recognizing real and fake faces. It shows how strong and reliable the proposed.

목차

Abstract
I. INTRODUCTION
II. LITERATURE REVIEW
III. PROPOSED METHODOLOGY
IV. RESULTS & DISCUSSION
V. CONCLUSION

키워드

저자

• Syed Muhammad Ali [ School of Computer Science National College of Business Administration and Economics, Lahore 54000, Pakistan ]
• Naila Sammar Naz [ School of Computer Science National College of Business Administration and Economics, Lahore 54000, Pakistan ]
• Muhammad Saleem [ School of Computer Science National College of Business Administration and Economics, Lahore 54000, Pakistan ]
• Muhammad Mazhar Ali [ School of Computer Science National College of Business Administration and Economics, Lahore 54000, Pakistan ]
• Fahad Ahmed [ School of Computer Science National College of Business Administration and Economics, Lahore 54000, Pakistan ]
• Muhammad Adnan Khan [ Faculty of Artificial Intelligence and Software Gachon University, Seongnam-si 13557, Republic of Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004