Profil

TOPAL Ali Osman

University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)

Main Referenced Co-authors
LEPREVOST, Franck  (8)
CHITIC, Ioana Raluca  (5)
Altun, Oguz (3)
MANCELLARI, Enea  (2)
Ali, Maaruf (1)
Main Referenced Keywords
Convolutional Neural Network (4); Black-box attack (3); Convolutional neural network (3); Evolutionary Algorithm (3); Black boxes (2);
Main Referenced Unit & Research Centers
ULHPC - University of Luxembourg: High Performance Computing (5)
Main Referenced Disciplines
Computer science (14)

Publications (total 15)

The most downloaded
225 downloads
Chitic, I. R., Topal, A. O., & Leprevost, F. (2021). Evolutionary Algorithm-based images, humanly indistinguishable and adversarial against Convolutional Neural Networks: efficiency and filter robustness. IEEE Access. doi:10.1109/ACCESS.2021.3131255 https://hdl.handle.net/10993/49149

The most cited

59 citations (OpenCitations)

Topal, A. O., & Altun, O. (22 March 2016). A novel meta-heuristic algorithm: dynamic virtual bats algorithm. Information Sciences, 354, 222-235. doi:10.1016/j.ins.2016.03.025 https://hdl.handle.net/10993/54985

LEPREVOST, F.* , TOPAL, A. O.* , MANCELLARI, E.* , & LAVANGNANANDA, K.*. (2023). Zone-of-Interest Strategy for the Creation of High-Resolution Adversarial Images Against Convolutional Neural Networks. In 2023 15th International Conference on Information Technology and Electrical Engineering, ICITEE 2023 (pp. 127-132). Institute of Electrical and Electronics Engineers Inc. doi:10.1109/ICITEE59582.2023.10317668
Peer reviewed
* These authors have contributed equally to this work.

Topal, A. O., Chitic, I. R., & Leprevost, F. (11 May 2023). One evolutionary algorithm deceives humans and ten convolutional neural networks trained on ImageNet at image recognition. Applied Soft Computing, 143, 110397. doi:10.1016/j.asoc.2023.110397
Peer Reviewed verified by ORBi

Chitic, I. R., Topal, A. O., & Leprevost, F. (22 March 2023). ShuffleDetect: Detecting Adversarial Images against Convolutional Neural Networks. Applied Sciences, 13 (6), 4068. doi:10.3390/app13064068
Peer Reviewed verified by ORBi

LEPREVOST, F., TOPAL, A. O., & MANCELLARI, E. (2023). Creating High-Resolution Adversarial Images Against Convolutional Neural Networks with the Noise Blowing-Up Method. In N. T. Nguyen & B. Hnatkowska (Eds.), Intelligent Information and Database Systems - 15th Asian Conference, ACIIDS 2023, Proceedings (pp. 121-134). Springer Science and Business Media Deutschland GmbH. doi:10.1007/978-981-99-5834-4_10
Peer reviewed

Leprevost, F., Topal, A. O., Avdusinovic, E., & Chitic, I. R. (2022). Strategy and Feasibility Study for the Construction of High Resolution Images Adversarial Against Convolutional Neural Networks. In ACIIDS 2022: Intelligent Information and Database Systems (pp. 285-298). Springer. doi:10.1007/978-3-031-21743-2_23
Peer reviewed

Leprevost, F., Topal, A. O., Avdusinovic, E., & Chitic, I. R. (22 October 2022). A strategy creating high-resolution adversarial images against convolutional neural networks and a feasibility study on 10 CNNs. Journal of Information and Telecommunication, 7 (1), 89-119. doi:10.1080/24751839.2022.2132586
Peer Reviewed verified by ORBi

Chitic, R., Topal, A. O., & Leprevost, F. (2022). Empirical Perturbation Analysis of Two Adversarial Attacks: Black Box versus White Box. Applied Sciences, 12 (14), 7339. doi:10.3390/app12147339
Peer reviewed

Chitic, I. R., Topal, A. O., & Leprevost, F. (2021). Evolutionary Algorithm-based images, humanly indistinguishable and adversarial against Convolutional Neural Networks: efficiency and filter robustness. IEEE Access. doi:10.1109/ACCESS.2021.3131255
Peer Reviewed verified by ORBi

Uka, A., Ndreu Halili, A., Polisi, X., Topal, A. O., Imeraj, G., & Vrana, N. E. (2021). Basis of Image Analysis for Evaluating Cell Biomaterial Interaction Using Brightfield Microscopy. Cells Tissues Organs, 210 (2), 77-104. doi:10.1159/000512969
Peer reviewed

Begaj, S., Topal, A. O., Ali, M., Ali, M., Miraz, M. H., Ware, A., & Soomro, S. (2020). Emotion Recognition Based on Facial Expressions Using Convolutional Neural Network (CNN). Proceedings - 2020 International Conference on Computing, Networking, Telecommunications and Engineering Sciences Applications, CoNTESA 2020, 58-63. doi:10.1109/CoNTESA50436.2020.9302866
Peer reviewed

Yildiz, Y. E., & Topal, A. O. (2019). Large scale continuous global optimization based on micro differential evolution with local directional search. Information Sciences, 477, 533--544. doi:10.1016/j.ins.2018.10.046
Peer reviewed

Koç, O., Tosku, L., Hoxha, J., Topal, A. O., Ali, M., & Uka, A. (2019). Detailed Analysis of IRIS Recognition Performance. In 2019 International Conference on Computing, Electronics Communications Engineering (iCCECE) (pp. 253--258). IEEE. doi:10.1109/iCCECE46942.2019.8941784
Peer reviewed

Topal, A. O., & Altun, O. (22 March 2016). A novel meta-heuristic algorithm: dynamic virtual bats algorithm. Information Sciences, 354, 222-235. doi:10.1016/j.ins.2016.03.025
Peer Reviewed verified by ORBi

Topal, A. O., Altun, O., & Terolli, E. (2014). Dynamic virtual bats algorithm (dvba) for minimization of supply chain cost with embedded risk. In 2014 European Modelling Symposium (pp. 58--64). IEEE. doi:10.1109/EMS.2014.52
Peer reviewed

Topal, A. O., & Altun, O. (2014). Dynamic virtual bats algorithm (dvba) for global numerical optimization. In A. O. Topal & O. Altun, 2014 International Conference on Intelligent Networking and Collaborative Systems (pp. 320--327). IEEE. doi:10.1109/INCoS.2014.40
Peer reviewed

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