activity
20182022
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 7 of their papers we have counts for

collaborators

8 papers

cs.CV2022

Lost in Compression: the Impact of Lossy Image Compression on Variable Size Object Detection within Infrared Imagery

Neelanjan Bhowmik, Jack W. Barker, Yona Falinie A. Gaus +1

Lossy image compression strategies allow for more efficient storage and transmission of data by encoding data to a reduced form. This is essential enable training with larger datas…

cs.CV2021

Operationalizing Convolutional Neural Network Architectures for Prohibited Object Detection in X-Ray Imagery

Thomas W. Webb, Neelanjan Bhowmik, Yona Falinie A. Gaus +1

The recent advancement in deep Convolutional Neural Network (CNN) has brought insight into the automation of X-ray security screening for aviation security and beyond. Here, we exp…

cs.CV2021

On the impact of using X-ray energy response imagery for object detection via Convolutional Neural Networks

Neelanjan Bhowmik, Yona Falinie A. Gaus, Toby P. Breckon

Automatic detection of prohibited items within complex and cluttered X-ray security imagery is essential to maintaining transport security, where prior work on automatic prohibited…

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.CV201917 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…