未明确命名

本研究未明确命名其创建的数据集，但该数据集是通过利用StyleGAN2生成模型和一种创新的进化搜索算法生成的。数据集旨在解决面部识别系统中的种族和人口统计多样性缺乏问题，包含50,000个身份每种族，总计1350万张图像。这些合成图像不包含任何个人可识别信息，提供了重要的隐私保护。数据集的应用领域是面部识别，旨在通过提供平衡的数据集来减少模型偏见，提高识别准确性。

This study did not explicitly name the dataset it created, which was generated using the StyleGAN2 generative model and an innovative evolutionary search algorithm. The dataset aims to address the lack of racial and demographic diversity in facial recognition systems, containing 50,000 identities per race and totaling 13.5 million images. These synthetic images do not contain any personally identifiable information (PII), providing robust privacy protection. The target application domain of this dataset is facial recognition, where it is intended to reduce model bias and improve recognition accuracy by supplying a balanced dataset.