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20182025
most citedThe Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composited X-ray Imagery

17 citations · 18 across the 10 of their papers we have counts for

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Showing 2019Show all

4 papers · 1 filter

cs.CV2019

Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery

Yona Falinie A. Gaus, Neelanjan Bhowmik, Samet Akcay +1

X-ray imagery security screening is essential to maintaining transport security against a varying profile of threat or prohibited items. Particular interest lies in the automatic d…

cs.CV2019

On the Impact of Object and Sub-component Level Segmentation Strategies for Supervised Anomaly Detection within X-ray Security Imagery

Neelanjan Bhowmik, Yona Falinie A. Gaus, Samet Akcay +2

X-ray security screening is in widespread use to maintain transportation security against a wide range of potential threat profiles. Of particular interest is the recent focus on t…

cs.CV2019★ 17 cited

The Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composited X-ray Imagery

Neelanjan Bhowmik, Qian Wang, Yona Falinie A. Gaus +2

Detecting prohibited items in X-ray security imagery is pivotal in maintaining border and transport security against a wide range of threat profiles. Convolutional Neural Networks…

cs.CV2019

Evaluation of a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery

Yona Falinie A. Gaus, Neelanjan Bhowmik, Samet Akçay +3

X-ray baggage security screening is widely used to maintain aviation and transport security. Of particular interest is the focus on automated security X-ray analysis for particular…