论文标题
新兴生物识别技术：深度推理和其他计算智能
Emerging Biometrics: Deep Inference and Other Computational Intelligence
论文作者
论文摘要
本文旨在确定新兴的计算智能趋势，以设计和建模复杂的生物特征识别基础架构和系统。生物特征识别系统正在使用自适应计算的原理（现代计算智能域的前潮）发展朝着深度学习和深度推理发展。因此，我们专注于广泛部署生物识别技术的智能推理引擎。选择了使用生理和行为特征涵盖各种生物识别任务的计算智能应用程序进行插图。我们强调了必须在子孙后代的生物识别系统中解决的技术差距。报告的方法和结果主要针对旨在开发下一代智能生物特征识别系统的研究人员。
This paper aims at identifying emerging computational intelligence trends for the design and modeling of complex biometric-enabled infrastructure and systems. Biometric-enabled systems are evolving towards deep learning and deep inference using the principles of adaptive computing, - the front tides of the modern computational intelligence domain. Therefore, we focus on intelligent inference engines widely deployed in biometrics. Computational intelligence applications that cover a wide spectrum of biometric tasks using physiological and behavioral traits are chosen for illustration. We highlight the technology gaps that must be addressed in future generations of biometric systems. The reported approaches and results primarily address the researchers who work towards developing the next generation of intelligent biometric-enabled systems.
