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Advanced strategies for identification and prevention are required because of the major challenge posed by the growth of modified photos and videos in digital media. To solve this problem, this study investigates the use of artificial intelligence (AI) and deep learning. One of the study's main goals is to create and apply advanced algorithms that can recognise modified visual material. The paper also emphasises the significance of variety in datasets and the continuous difficulties in obtaining real-time detection skills. The ethical issues surrounding the creation and application of such technologies are explored, as well as techniques for preventing adversarial assaults on detection models.

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Advanced Algorithms to Detect and Prevent the Spread of Manipulated Images and Videos Using Deep Learning and AI

  • 会议论文

  • 发表日期：

    2025年

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  • Divya Pachimatla,
  • Rampriya Kilari,
  • I. B. Ranitha,
  • Indur Ranaveer,
  • Katakam Srinivasa Rao,
  • Kummari Renuka

摘要

Advanced strategies for identification and prevention are required because of the major challenge posed by the growth of modified photos and videos in digital media. To solve this problem, this study investigates the use of artificial intelligence (AI) and deep learning. One of the study's main goals is to create and apply advanced algorithms that can recognise modified visual material. The paper also emphasises the significance of variety in datasets and the continuous difficulties in obtaining real-time detection skills. The ethical issues surrounding the creation and application of such technologies are explored, as well as techniques for preventing adversarial assaults on detection models.