Investigating tensorflow for airport facial identification: poster
5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security (HotSOS'18)
Contributing USMA Research Unit(s)
Cyber Research Center, Electrical Engineering and Computer Science
Facial recognition is a rapidly developing application of machine learning. Face identification is specifically being adopted across security systems such as airports, perimeter security, and law-enforcement. In this poster, we describe a facial identification approach that can be deployed at airports. Our contributions include i.) facial identification software built on top of Google's TensorFlow  framework; ii.) a data collection scheme that can be implemented at airports nationally; and iii.) a user interface for collecting data.
Nikolay Shopov, Mingu Jeong, Evin Rude, Brennan Neseralla, Scott Hutchison, Alexander Mentis, and Suzanne J. Matthews. 2018. Investigating tensorflow for airport facial identification: poster. In Proceedings of the 5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security (HoTSoS '18). ACM, New York, NY, USA, Article 23, 1 pages. DOI: https://doi.org/10.1145/3190619.3191692
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