Investigating tensorflow for airport facial identification

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 [1] framework; ii.) a data collection scheme that can be implemented at airports nationally; and iii.) a user interface for collecting data.
Security and privacy, Computing methodologies, Artificial intelligence, Machine learning
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). Association for Computing Machinery, New York, NY, USA, Article 23, 1.