
Title
Investigating tensorflow for airport facial identification: poster
Event
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
Description
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.
Publication Date
Spring 4-2018
Document Type
Presentation/Poster
Recommended Citation
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
Files
Download Full Text

Record links to items hosted by external providers may require fee for full-text.