通过基于云的API进行面部识别,以手术辅助快速部扩张为基础
Muhammed Hilmi Buyukcavus1, Filiz Aydogan Akgun2, Serdar Solak3
1Faculty of Dentistry, Department of Orthodontics, Antalya Bilim University, Antalya, Turkey. mhbuyukcvs@gmail.com.
概括
面部识别软件在手术辅助快速上扩张 (SARME) 后检测到变化. 微笑着的照片显示了更高的相似度得分,而个人资料显示得分更低,表明了面部软组织的改变.
科学领域:
- 矯正牙醫和牙臉整形醫學
- 计算机科学和人工智能 人工智能
背景情况:
- 手术辅助快速大扩张 (SARME) 是一种扩大口的手术.
- 在SARME后面部软组织的变化尚未完全理解.
- 面部生物识别应用程序被广泛用于识别.
研究的目的:
- 评估SARME后面部软组织的变化是否可以通过面部生物识别应用程序检测到.
- 为了比较三个不同的面部识别API在检测这些变化的性能.
主要方法:
- 在使用AWS Rekognition,Microsoft Azure Cognitive和Face++ API分析了22名患者的SARME前后照片.
- 类似性得分计算了放松,微笑,个人资料和半个人资料的观点.
- 统计分析包括弗里德曼测试,威尔科克森签名等级测试和斯皮尔曼相关性.
主要成果:
- 在三个测试的面部识别程序中,SARME显著改变了面部相似性得分.
- 与AWS Rekognition和微软Azure相比,Face++的相似性得分较低. 这是一个很好的例子.
- 微笑照片的相似度比其他视图高,但在统计学上有显著差异.
结论:
- 面部识别API可以检测SARME后的软组织变化.
- 微笑的面部图像在检测后SARME变化时更敏感.
- 个人资料显示的相似度得分最低,这表明这个面部方面发生了显著的变化.
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