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通过对抗性训练增强牙损伤的分类,对咬牙X射线图进行训练

Wattanapong Suttapak1, Wannakamon Panyarak2, Arnon Charuakkra2

  • 1Division of Computer Engineering, School of Information and Communication Technology, University of Phayao, Phayao, Thailand.

Journal of imaging informatics in medicine
|November 10, 2025
PubMed
概括

这项研究通过使用深度学习模型来提高牙损伤的分类,这些模型经过预测梯度下降 (PGD) 的训练. 使用PGD进行对抗训练可以提高AI的准确性和稳定性,用于从放射图片中诊断腔.

关键词:
产生对抗性攻击的攻击.脏病诊断 脏病诊断 脏病诊断牙虫的分类 牙虫的分类预计的梯度下降 (PGD)这就是ResNet ResNet.

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相关概念视频

X-ray Imaging01:24

X-ray Imaging

German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with X-rays, and by 1900, X-ray was widely...