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相关概念视频

Prosopagnosia01:24

Prosopagnosia

181
Prosopagnosia, also known as face blindness, is the inability to recognize faces. In severe cases, individuals with prosopagnosia may not recognize close family members, including parents and spouses, by their faces. For instance, someone with prosopagnosia might walk past their child in a crowd, only realizing their mistake upon noticing their child's distinctive backpack or favorite jacket. Prosopagnosia specifically impairs facial recognition, while the recognition of other objects or...
181

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AuCFSR:使用新的2D超混沌系统和深度学习模型进行身份验证和颜色面部自我恢复.

Achraf Daoui1, Mohamed Yamni2, Torki Altameem3

  • 1National School of Applied Sciences, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco.

Sensors (Basel, Switzerland)
|November 14, 2023
PubMed
概括

这项研究介绍了Authentication and Color Face Self-Recovery (AuCFSR) 一种新的方法,用于保护彩色面部图像免受改. AuCFSR确保图像的真实性,并使用超混沌系统和深度学习模型恢复改变的部分.

关键词:
彩色图像身份验证 颜色图像身份验证深度学习模型的深度学习模型脆弱的水印是脆弱的水印过度混乱的系统.自己恢复的自我恢复.改检测 改检测 改检测

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科学领域:

  • 数字图像法医学 数字图像法医学
  • 网络安全 网络安全
  • 计算机视觉 计算机视觉

背景情况:

  • 通过公共网络传输的彩色面部图像容易受到恶意改.
  • 现有的方法可能缺乏强大的身份验证和有效的恢复能力,以妥协的面部图像.

研究的目的:

  • 开发一种新的方案,即身份验证和颜色面部自我恢复 (AuCFSR),用于验证颜色面部图像和恢复改的区域.
  • 增强数字面部数据的安全性和完整性,防止未经授权的修改.

主要方法:

  • AuCFSR使用一种新的二维模块化正弦-正弦图 (2D MSCM) 超混沌系统嵌入身份验证和恢复数据.
  • 数据隐藏在颜色图像像像素中最不重要的位中.
  • 深度学习模型,CodeFormer和DeOldify,用于恢复图像的视觉增强和彩色化.

主要成果:

  • 拟议的AuCFSR计划有效地检测了改的彩色面部图像.
  • 它实现了高水平的安全性,并产生高质量的输出图像.
  • 恢复后的图像显示出更好的视觉质量和色彩.

结论:

  • 与现有方案相比,AuCFSR在改检测准确性,安全性和视觉恢复方面提供了卓越的性能.
  • 超混沌系统和深度学习的集成为彩色面部图像身份验证和自我恢复提供了强大的解决方案.