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On the Impact of Object and Sub-component Level Segmentation Strategies for Supervised Anomaly Detection within X-ray Security Imagery., , , , and . CoRR, (2019)Threat Object-based anomaly detection in X-ray images using GAN-based ensembles., , and . Neural Comput. Appl., 35 (31): 23025-23040 (November 2023)Unaligned 2D to 3D Translation with Conditional Vector-Quantized Code Diffusion using Transformers., , , , , , and . ICCV, page 14539-14548. IEEE, (2023)Evaluating the Transferability and Adversarial Discrimination of Convolutional Neural Networks for Threat Object Detection and Classification within X-Ray Security Imagery., , , and . ICMLA, page 420-425. IEEE, (2019)1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results., , , , , , , , , and 62 other author(s). WACV (Workshops), page 265-302. IEEE, (2023)The Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composited X-ray Imagery., , , , and . CoRR, (2019)On the Impact of Using X-Ray Energy Response Imagery for Object Detection Via Convolutional Neural Networks., , and . ICIP, page 1224-1228. IEEE, (2021)Robust Semi-Supervised Anomaly Detection via Adversarially Learned Continuous Noise Corruption., , , and . VISIGRAPP (5: VISAPP), page 615-625. SCITEPRESS, (2023)On the Impact of Object and Sub-Component Level Segmentation Strategies for Supervised Anomaly Detection within X-Ray Security Imagery., , , , and . ICMLA, page 986-991. IEEE, (2019)Semi-Supervised Surface Anomaly Detection of Composite Wind Turbine Blades From Drone Imagery., , and . CoRR, (2021)