| Evaluation of a dual convolutional neural network architecture for object-wise anomaly detection in cluttered X-ray security imagery YFA Gaus, N Bhowmik, S Akçay, PM Guillen-Garcia, JW Barker, ... 2019 international joint conference on neural networks (IJCNN), 1-8, 2019 | 72 | 2019 |
| On the impact of object and sub-component level segmentation strategies for supervised anomaly detection within x-ray security imagery N Bhowmik, YFA Gaus, S Akçay, JW Barker, TP Breckon 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 25 | 2019 |
| Lost in compression: the impact of lossy image compression on variable size object detection within infrared imagery N Bhowmik, JW Barker, YFA Gaus, TP Breckon Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 10 | 2022 |
| Panda: Perceptually aware neural detection of anomalies JW Barker, TP Breckon 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 7 | 2021 |
| Semi-Supervised Surface Anomaly Detection of Composite Wind Turbine Blades From Drone Imagery J Barker, N Bhowmik, T Breckon arXiv preprint arXiv:2112.00556, 2021 | 3 | 2021 |
| Robust semi-supervised anomaly detection via adversarially learned continuous noise corruption JW Barker, N Bhowmik, YFA Gaus, TP Breckon arXiv preprint arXiv:2303.03925, 2023 | 2 | 2023 |
| Semi-Supervised Deep Learning Approaches for Anomaly Detection in Computer Vision J BARKER Durham University, 2023 | | 2023 |
