| 2025 | CVPR | Beyond Academic Benchmarks: Critical Analysis and Best Practices for Visual Industrial Anomaly Detection. | Aimira Baitieva, Yacine Bouaouni, Alexandre Briot, Dick Ameln, Souhaiel Khalfaoui, Samet Akcay |
| 2025 | ICCV | FEVER-OOD: Free Energy Vulnerability Elimination for Robust Out-of-Distribution Detection. | Brian K. S. Isaac-Medina, Mauricio Che, Yona Faline A. Gaus, Samet Akcay, Toby P. Breckon |
| 2024 | BMVC | AUPIMO: Redefining Anomaly Localization Benchmarks with High Speed and Low Tolerance. | Joo P. C. Bertoldo, Dick Ameln, Ashwin Vaidya, Samet Akcay |
| 2024 | CVPR | Divide and Conquer: High-Resolution Industrial Anomaly Detection via Memory Efficient Tiled Ensemble. | Blaz Rolih, Dick Ameln, Ashwin Vaidya, Samet Akcay |
| 2022 | ICIP | Anomalib: A Deep Learning Library for Anomaly Detection. | Samet Akcay, Dick Ameln, Ashwin Vaidya, Barath Lakshmanan, Nilesh A. Ahuja, Ergin Utku Genc |
| 2019 | ICMLA | 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, Toby P. Breckon |
| 2018 | ACCV | GANomaly: Semi-supervised Anomaly Detection via Adversarial Training. | Samet Akcay, Amir Atapour Abarghouei, Toby P. Breckon |
| 2018 | ICIP | On the Impact of Varying Region Proposal Strategies for Raindrop Detection and Classification Using Convolutional Neural Networks. | Tiancheng Guo, Samet Akcay, Philip A. Adey, Toby P. Breckon |
| 2017 | ICIP | An evaluation of region based object detection strategies within X-ray baggage security imagery. | Samet Akcay, Toby P. Breckon |
| 2016 | ICIP | Transfer learning using convolutional neural networks for object classification within X-ray baggage security imagery. | Samet Akcay, Mikolaj E. Kundegorski, Michael Devereux, Toby P. Breckon |