论文标题
多样性和新颖大师：生成多个DeepMasterPrints以增加用户覆盖范围
Diversity and Novelty MasterPrints: Generating Multiple DeepMasterPrints for Increased User Coverage
论文作者
论文摘要
这项工作扩大了遗传指纹欺骗的先前进步，并引入了多样性和新颖大师。该系统使用质量多样性进化算法来生成人造印刷的字典，重点是增加数据集对用户的覆盖范围。多样性主版物的重点是生成与以前发现的印刷品所涵盖的用户相匹配的解决方案打印，而新颖的主版印刷明确地搜索了与以前的印刷品相比，在用户空间中更多的印刷品。我们的多印刷搜索方法在覆盖范围和概括方面都超过了奇异的深层印刷，同时保持指纹图像输出的质量。
This work expands on previous advancements in genetic fingerprint spoofing via the DeepMasterPrints and introduces Diversity and Novelty MasterPrints. This system uses quality diversity evolutionary algorithms to generate dictionaries of artificial prints with a focus on increasing coverage of users from the dataset. The Diversity MasterPrints focus on generating solution prints that match with users not covered by previously found prints, and the Novelty MasterPrints explicitly search for prints with more that are farther in user space than previous prints. Our multi-print search methodologies outperform the singular DeepMasterPrints in both coverage and generalization while maintaining quality of the fingerprint image output.
