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Artificial Intelligence for Biometric Technologies and Systems
July 28, 2021 @ 4:00 pm - 5:00 pm
ABSTRACT: Biometrics concerns the study of automated methods for identifying an individual by measuring one or more physical or behavioral features of him. Nowadays biometrics is getting more and more accurate in identifying persons and behaviors. Artificial intelligence techniques have been proved to be useful and effective in addressing this kind of data processing. This talk will review the domain of biometrics, its applications in various domains and the relevance of artificial intelligence, in particular neural networks and deep learning, to effectively solve various problems in these applications.
报告摘要:生物特征识别技术是一种通过衡量人类个体的一个或多个物理或行为特征来识别其身份的自动化方法。如今,生物特征识别技术在识别人和行为方面越来越精确。人工智能技术已被证明在解决这类数据处理问题上是确有实效的。本次报告将回顾生物识别及其在各个领域的应用,以及它与人工智能的相关性,特别是神经网络和深度学习,以有效地解决这些应用中的各种问题。
BIOGRAPHY: Vincenzo Piuri is Full Professor in computer engineering at the University of Milan, Italy (since 2000). He is Fellow of the IEEE, Distinguished Scientist of ACM, and Senior Member of INNS. He is President of the IEEE Systems Council (2020-21) and IEEE Region 8 Director-elect (2021-22). He received the IEEE Instrumentation and Measurement Society Technical Award (2002) and the IEEE TAB Hall of Honor (2019). His main research interests are: artificial intelligence, computational intelligence, intelligent systems, machine learning, pattern analysis and recognition, signal and image processing, biometrics, intelligent measurement systems, industrial applications, digital processing architectures, fault tolerance, cloud computing infrastructures, and internet-of-things. Original results have been published in 400+ papers in international journals, proceedings of international conferences, books, and book chapters.
报告人介绍:Vincenzo Piuri是意大利米兰大学计算机工程系的全职教授(自2000以来)。他是IEEE fellow,ACM的杰出科学家,INNS的高级成员。他是IEEE Systems Council主席(2020-21年)和IEEE Region 8的 Director-elect(2021-22年)。他获得了IEEE Instrumentation and Measurement Society Technical Award(2002年)和IEEE TAB Hall of Honor(2019年)。其主要研究方向为:人工智能、计算智能、智能系统、机器学习、模式分析与识别、信号与图像处理、生物特征识别、智能测量系统、工业应用、数字处理架构、容错、云计算基础设施,以及物联网。他已在国际期刊、国际会议发表400多篇论文,并且有多部相关领域的著作。