论文标题
人口偏见：Fingerverin识别系统的挑战？
Demographic Bias: A Challenge for Fingervein Recognition Systems?
论文作者
论文摘要
最近，人们对许多自动化系统（包括生物识别技术）的潜在偏见的担忧已经提出。在这种情况下，一种有偏见的算法会根据某些人（通常受反歧视立法保护）属性（例如性别和年龄保护）为不同的个体产生统计上不同的结果。尽管确实存在一些针对面部识别算法进行调查此问题的初步研究，但尚未针对血管生物识别特征介绍主题。因此，在本文中，对几种流行的识别算法进行了基准测试，以确定该问题以识别。实验评估表明，测试算法缺乏偏差，尽管需要使用较大数据集的未来工作来验证和确认这些初步结果。
Recently, concerns regarding potential biases in the underlying algorithms of many automated systems (including biometrics) have been raised. In this context, a biased algorithm produces statistically different outcomes for different groups of individuals based on certain (often protected by anti-discrimination legislation) attributes such as sex and age. While several preliminary studies investigating this matter for facial recognition algorithms do exist, said topic has not yet been addressed for vascular biometric characteristics. Accordingly, in this paper, several popular types of recognition algorithms are benchmarked to ascertain the matter for fingervein recognition. The experimental evaluation suggests lack of bias for the tested algorithms, although future works with larger datasets are needed to validate and confirm those preliminary results.
