Toward Automatic Threat Recognition for Airport X-ray Baggage Screening\n with Deep Convolutional Object Detection Article Swipe

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Kevin J Liang , John B. Sigman , Gregory P. Spell , D. A. Strellis , William S. C. Chang , Felix Liu , Tejas S. Mehta , Lawrence Carin ·

YOU? · · 2019 · Open Access · · DOI: https://doi.org/10.48550/arxiv.1912.06329

For the safety of the traveling public, the Transportation Security\nAdministration (TSA) operates security checkpoints at airports in the United\nStates, seeking to keep dangerous items off airplanes. At these checkpoints,\nthe TSA employs a fleet of X-ray scanners, such as the Rapiscan 620DV, so\nTransportation Security Officers (TSOs) can inspect the contents of carry-on\npossessions. However, identifying and locating all potential threats can be a\nchallenging task. As a result, the TSA has taken a recent interest in deep\nlearning-based automated detection algorithms that can assist TSOs. In a\ncollaboration funded by the TSA, we collected a sizable new dataset of X-ray\nscans with a diverse set of threats in a wide array of contexts, trained\nseveral deep convolutional object detection models, and integrated such models\ninto the Rapiscan 620DV, resulting in functional prototypes capable of\noperating in real time. We show performance of our models on held-out\nevaluation sets, analyze several design parameters, and demonstrate the\npotential of such systems for automated detection of threats that can be found\nin airports.\n

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Task (project management) Computer science Object detection Set (abstract data type) Public security Deep learning Airport security Artificial intelligence Convolutional neural network Object (grammar) Computer security Pattern recognition (psychology) Engineering Systems engineering Programming language Political science Public administration

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/1912.06329
PDF: https://arxiv.org/pdf/1912.06329
OA Status: green
Cited By: 31
Related Works: 10
OpenAlex ID: https://openalex.org/W4287994947

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DOI: https://doi.org/10.48550/arxiv.1912.06329

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Title: Toward Automatic Threat Recognition for Airport X-ray Baggage Screening\n with Deep Convolutional Object Detection

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Type: preprint

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Language: en

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Publication year: 2019

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Publication date: 2019-12-13

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Authors: Kevin J Liang, John B. Sigman, Gregory P. Spell, D. A. Strellis, William S. C. Chang, Felix Liu, Tejas S. Mehta, Lawrence Carin

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Landing page: https://arxiv.org/abs/1912.06329

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Concepts: Task (project management), Computer science, Object detection, Set (abstract data type), Public security, Deep learning, Airport security, Artificial intelligence, Convolutional neural network, Object (grammar), Computer security, Pattern recognition (psychology), Engineering, Systems engineering, Programming language, Political science, Public administration

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Cited by: 31

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citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False