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Threat Detection in Baggage Scans

Publications

Journals

  • Enhancing security in X-ray baggage scans: A contour-driven learning approach for abnormality classification and instance segmentation Engineering Applications of Artificial Intelligence, D Velayudhan, A Ahmed, T Hassan, N Gour, M Owais, M Bennamoun,2024 [pdf] [Demo]
  • Autonomous Localization of X-Ray Baggage Threats via Weakly Supervised Learning IEEE Transactions on Industrial Informatics, D Velayudhan, A Ahmed, T Hassan, N Gour, M Owais, M Bennamoun,2024 [pdf] [Demo]
  • Recent advances in baggage threat detection: A comprehensive and systematic survey. ACM Computing Surveys. Velayudhan, D., Hassan, T., Damiani, E., and Werghi, N., 2022. [pdf]
  • A novel incremental learning-driven instance segmentation framework to recognize highly cluttered instances of the contraband items. IEEE Transactions on Systems, Man, and Cybernetics: Systems. Hassan, T., Akcay, S., Bennamoun, M., Khan, S., and Werghi, N., 2021. [pdf] [demo]
  • Cascaded structure tensor for robust baggage threat detection. Neural Computing and Applications. Hassan, T., Akcay, S., Hassan, B., Bennamoun, M., Khan, S., Dias, J., and Werghi, N., 2023. [pdf] [demo]
  • Unsupervised anomaly instance segmentation for baggage threat recognition. Journal of Ambient Intelligence and Humanized Computing. Hassan, T., Akcay, S., Bennamoun, M., Khan, S., and Werghi, N., 2021. [pdf] [demo]
  • Tensor pooling-driven instance segmentation framework for baggage threat recognition. Neural Computing and Applications. Hassan, T., Akcay, S., Bennamoun, M., Khan, S., and Werghi, N., 2022. [pdf] [demo]
  • Programmable broad learning system for baggage threat recognition. Multimedia Tools and Applications. Shafay, M., Ahmed, A., Hassan, T., Dias, J., and Werghi, N., 2023. [pdf] [demo]
  • Meta-transfer learning driven tensor-shot detector for the autonomous localization and recognition of concealed baggage threats. Sensors. Hassan, T., Shafay, M., Akcay, S., Khan, S., Bennamoun, M., Damiani, E., and Werghi, N., 2020. [demo]

Conferences

  • Trainable structure tensors for autonomous baggage threat detection under extreme occlusion. Proceedings of the Asian Conference on Computer Vision. Hassan, T., and Werghi, N., 2020. [pdf] [demo]
  • Context-Aware Transformers for Weakly Supervised Baggage Threat Localization. 2023 IEEE International Conference on Image Processing (ICIP). Velayudhan, D., Ahmed, A., Hassan, T., Bennamoun, M., Damiani, E., and Werghi, N., 2023. [pdf] [demo]
  • Balanced affinity loss for highly imbalanced baggage threat contour-driven instance segmentation. 2022 IEEE International Conference on Image Processing (ICIP). Ahmed, A., Obeid, A., Velayudhan, D., Hassan, T., Damiani, E., and Werghi, N., 2022. [pdf] [demo]
  • Incremental Instance Segmentation for Cluttered Baggage Threat Detection. 2023 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA). Nasim, A., Velayudhan, D., Ahmed, A.H., Hassan, T., Akcay, S., Akram, M.U., and Werghi, N., 2023. [pdf] [demo]
  • Highly imbalanced baggage threat classification. 2023 15th International Conference on Machine Learning and Computing. Ahmed, A., Velayudhan, D., Hassan, T., Bennamoun, M., Damiani, E., and Werghi, N., 2023. [pdf] [demo]
  • Detection Transformer Framework for Recognition of Heavily Occluded Suspicious Objects. 2023 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA). Ahmed, A., Alansari, M., Alnuaimi, K., Velayudhan, D., Hassan, T., and Werghi, N., 2023. [pdf] [demo]
  • An Ensemble Learning Method Based on Deep Neural and Pca-Based Svm Network for Baggage Threat and Smoke Recognition. 2023 Advances in Science and Engineering Technology International Conferences (ASET). Ahmed, A.H., Al Radi, M., and Werghi, N., 2023. [pdf] [demo]
  • Transformers for Imbalanced Baggage Threat Recognition. 2022 IEEE International Symposium on Robotic and Sensors Environments (ROSE). Velayudhan, D., Ahmed, A.H., Hassan, T., Bennamoun, M., Damiani, E., and Werghi, N., 2022. [pdf] [demo]
  • Baggage threat recognition using deep low-rank broad learning detector. 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON). Velayudhan, D., Hassan, T., Ahmed, A.H., Damiani, E., and Werghi, N., 2022. [pdf] [demo]
  • Programmable broad learning system to detect concealed and imbalanced baggage threats. 2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2). Shafay, M., Hassan, T., Ahmed, A., Velayudhan, D., Dias, J., and Werghi, N., 2022. [pdf] [demo]
  • Baggage threat detection under extreme class imbalance. 2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2). Ahmed, A., Velayudhan, D., Hassan, T., Hassan, B., Dias, J., and Werghi, N., 2022. [pdf] [demo]
  • Temporal fusion based multi-scale semantic segmentation for detecting concealed baggage threats. 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC). Shafay, M., Hassan, T., Damiani, E., and Werghi, N., 2021. [pdf] [demo]
  • Detecting prohibited items in X-ray images: A contour proposal learning approach. 2020 IEEE International Conference on Image Processing (ICIP). Hassan, T., Bettayeb, M., Akçay, S., Khan, S., Bennamoun, M., and Werghi, N., 2020. [pdf] [demo]
  • Cascaded structure tensor framework for robust identification of heavily occluded baggage items from X-ray scans. arXiv preprint arXiv:2004.06780. Hassan, T., Akcay, S., Bennamoun, M., Khan, S., and Werghi, N., 2020. [pdf] [demo]
  • Deep CMST framework for the autonomous recognition of heavily occluded and cluttered baggage items from multivendor security radiographs. CoRR, 14, p.17. Hassan, T., Khan, S.H., Akcay, S., Bennamoun, M., and Werghi, N., 2019. [pdf] [demo]
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