PUBLICATIONS

1. Bi, P., Chen, M., Du, X., Sohrab, F., & Gabbouj, M. (2025). Double Layer Robust 2DPCA: Joint Flexible Cut Norm and Adaptive Weighted Learning for Small Sample Size Image Recognition. IEEE Transactions on Consumer Electronics.

2. Chaudhry, F. M., Ralli, J., Leudet, J., Sohrab, F., Pakdaman, F., Corbani, P., & Gabbouj, M. (2025). Deep-BrownConrady: Prediction of Camera Calibration and Distortion Parameters Using Deep Learning and Synthetic Data. IEEE Transactions on Automation Science and Engineering.

3. Khan, T., Sohrab, F., Michalas, A., & Gabbouj, M. (2025, April). To Vaccinate or Not to Vaccinate? Analyzing X Power over the Pandemic. In International Conference on Advanced Information Networking and Applications (pp. 352-365). Cham: Springer Nature Switzerland.

4. Kilickaya, S., Ahishali, M., Celebioglu, C., Sohrab, F., Eren, L., Ince, T., ... & Gabbouj, M. (2025, March). Audio-based anomaly detection in industrial machines using deep one-class support vector data description. In 2025 IEEE Symposium on Computational Intelligence on Engineering/Cyber Physical Systems Companion (CIES Companion) (pp. 1-5). IEEE. 

5. Laakom, F., Sohrab, F., Raitoharju, J., Iosifidis, A., & Gabbouj, M. (2025, March). Convolutional autoencoder-based multimodal one-class classification. In 2025 IEEE Symposium on Computational Intelligence in Image, Signal Processing and Synthetic Media Companion (CISM Companion)  (pp. 1-5). IEEE. 

6. Zahid, M. U., Degerli, A., Sohrab, F., Kiranyaz, S., Hamid, T., Mazhar, R., & Gabbouj, M. (2024, October). Refining Myocardial Infarction Detection: A Novel Multi-Modal Composite Kernel Strategy in One-Class Classification. In 2024 IEEE International Conference on Image Processing (ICIP) (pp. 3010-3016). IEEE.

7. Al-Khshali, H. H., Ilyas, M., Sohrab, F., & Gabbouj, M. (2024). Malware Detection with Subspace Learning-based One-Class Classification. IEEE Access.

8. Khan, T., Sohrab, F., Michalas, A., & Gabbouj, M. (2024, April). Trustworthiness of X Users: A One-Class Classification Approach. In International Conference on Advanced Information Networking and Applications (pp. 331-343). Springer.

9. Sohrab, F., Laakom, F., & Gabbouj, M. (2023, December). Newton Method-based Subspace Support Vector Data Description. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1372-1379). IEEE.

10. Guidry, J., Sohrab, F., Gottumukkala, R., Katragadda, S., & Gabbouj, M. (2023, December). One-Class Classification for Intrusion Detection on Vehicular Networks. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1176-1182). IEEE.

11. Zaffar, Z., Sohrab, F., Kanniainen, J., & Gabbouj, M. (2023, December). Credit Card Fraud Detection with Subspace Learning-based One-Class Classification. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 407-412). IEEE.

12. Kemell, K. K., Vakkuri, V., & Sohrab, F. (2023). How Do AI Ethics Principles Work? From Process to Product Point of View. In Conference on Technology Ethics, Tethics (pp. 24-38). CEUR-WS.

13. Devecioglu, O., Ahishali, M., Sohrab, F., Ince, T., & Gabbouj, M. (2023). Improved Active Fire Detection Using Operational U-nets. In Photonics & Electromagnetics Research Symposium (PIERS), Prague, Czech Republic, 2023, pp. 692-697 

14. Kilickaya, S., Ahishali, M., Sohrab, F., Ince, T., & Gabbouj, M. (2023). Hyperspectral Image Analysis with Subspace Learning-based One-Class Classification. In Photonics & Electromagnetics Research Symposium (PIERS), Prague, Czech Republic, 2023, pp. 953-959 

15. Sohrab, F., Iosifidis, A., Gabbouj, M., & Raitoharju, J. (2023). Graph-embedded subspace support vector data description. Pattern Recognition, 133, 108999. 

16. Degerli, A., Sohrab, F., Kiranyaz, S., & Gabbouj, M. (2022, September). Early Myocardial Infarction Detection with One-Class Classification over Multi-view Echocardiography. In 2022 Computing in Cardiology (CinC) (Vol. 498, pp. 1-4). IEEE.

17. Zhang, K., Wang, B., Wang, W., Sohrab, F., Gabbouj, M., & Kuo, C. C. J. (2021, December). Anomalyhop: an ssl-based image anomaly localization method. In 2021 International Conference on Visual Communications and Image Processing (VCIP) (pp. 1-5). IEEE. 

18. Sohrab, F., Raitoharju, J., Iosifidis, A., & Gabbouj, M. (2021). Multimodal subspace support vector data description. Pattern Recognition, 110, 107648. 

19. Sohrab, F., & Raitoharju, J. (2020, December). Boosting rare benthic macroinvertebrates taxa identification with one-class classification. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 928-933). IEEE.

20. Sohrab, F., Raitoharju, J., & Gabbouj, M. (2020, September). Facial expression based satisfaction index for empathic buildings. In Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers (pp. 704-707).

21. Sohrab, F., Raitoharju, J., Iosifidis, A., & Gabbouj, M. (2020). Ellipsoidal subspace support vector data description. IEEE Access, 8, 122013-122025.

22. Sohrab, F., Raitoharju, J., Gabbouj, M., & Iosifidis, A. (2018, August). Subspace support vector data description. In 2018 24th International Conference on Pattern Recognition (ICPR) (pp. 722-727). IEEE.

23. Sohrab, F., & Erdogan, H. (2015, August). Recognize and separate approach for speech denoising using nonnegative matrix factorization. In 2015 23rd European Signal Processing Conference (EUSIPCO) (pp. 1083-1087). IEEE.

arXiv / Paper(s) under review

24. Hosseini, M., Sohrab, F., Gottumukkala, R., Bhupatiraju, R. T., Katragadda, S., Raitoharju, J., Iosifidis, A., & Gabbouj, M. (2022). EmpathicSchool: A multimodal dataset for real-time facial expressions and physiological data analysis under different stress conditions. ArXiv. /abs/2209.13542

25. Liang, A., Liu, Q., Xu, L., Sohrab, F., Cui, W., Song, C., & Gaubbouj, M. (2024). Conformal Prediction on Quantifying Uncertainty of Dynamic Systems. arXiv preprint arXiv:2412.10459.

26. Debelle, T., Sohrab, F., Abrahamsson, P., & Gabbouj, M. (2025). Anomaly Detection in Smart Power Grids with Graph-Regularized MS-SVDD: a Multimodal Subspace Learning Approach. arXiv preprint arXiv:2502.15793.