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 Akçay; Jack W. Barker; Toby P. Breckon (ICMLA, 2019)

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; Paolo M. Guillén-Garcia; Jack W. Barker; Toby P. Breckon (IJCNN, 2019)

PANDA: Perceptually Aware Neural Detection of Anomalies. - Jack W. Barker; Toby P. Breckon (IJCNN, 2021)

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; Toby P. Breckon (CVPR Workshops, 2022)

Semi-supervised Surface Anomaly Detection of Composite Wind Turbine Blades from Drone Imagery. - Jack W. Barker; Neelanjan Bhowmik; Toby P. Breckon (VISIGRAPP (4: VISAPP), 2022)

Robust Semi-Supervised Anomaly Detection via Adversarially Learned Continuous Noise Corruption. - Jack W. Barker; Neelanjan Bhowmik; Yona Falinie A. Gaus; Toby P. Breckon (VISIGRAPP (5: VISAPP), 2023)