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MEJRI Nesryne

University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > CVI2

ORCID
0000-0002-0541-1234
Main Referenced Co-authors
AOUADA, Djamila  (8)
GHORBEL, Enjie  (3)
KACEM, Anis  (3)
CHERENKOVA, Kseniya  (2)
CHERNAKOV, Pavel  (2)
Main Referenced Keywords
Computer Science - Computer Vision and Pattern Recognition (2); cad (1); computer aided design (1); Computer Vision (1); constraint (1);
Main Referenced Unit & Research Centers
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > CVI² - Computer Vision Imaging & Machine Intelligence (5)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Computer Vision Imaging & Machine Intelligence (CVI²) (1)
Main Referenced Disciplines
Computer science (10)

Publications (total 10)

The most downloaded
206 downloads
MEJRI, N., PAPADOPOULOS, K., & AOUADA, D. (2021). Leveraging High-Frequency Components for Deepfake Detection. IEEE Workshop on Multimedia Signal Processing. doi:10.1109/MMSP53017.2021.9733606 https://hdl.handle.net/10993/48389

The most cited

8 citations (Scopus®)

MEJRI, N., DUPONT, E., & Da Costa, G. (2020). Energy-aware scheduling of malleable HPC applications using a Particle Swarm optimised greedy algorithm. Sustainable Computing: Informatics and Systems. doi:10.1016/j.suscom.2020.100447 https://hdl.handle.net/10993/48064

MEJRI, N., Laura Lopez-Fuentes, Kankana Roy, CHERNAKOV, P., GHORBEL, E., & AOUADA, D. (05 December 2024). Unsupervised anomaly detection in time-series: An extensive evaluation and analysis of state-of-the-art methods. Expert Systems with Applications, 256. doi:10.1016/j.eswa.2024.124922
Peer Reviewed verified by ORBi

KARADENIZ, A. S., MALLIS, D., MEJRI, N., CHERENKOVA, K., KACEM, A., & AOUADA, D. (04 December 2024). PICASSO: A Feed-Forward Framework for Parametric Inference of CAD Sketches via Rendering Self-Supervision [Paper presentation]. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Peer reviewed

KARADENIZ, A. S., MALLIS, D., MEJRI, N., CHERENKOVA, K., KACEM, A., & AOUADA, D. (30 October 2024). DAVINCI: A Single-Stage Architecture for Constrained CAD Sketch Inference [Paper presentation]. British Machine Vision Conference 2024, Glasgow, United Kingdom.
Peer reviewed

MEJRI, N., CHERNAKOV, P., KULESHOVA, P., GHORBEL, E., & AOUADA, D. (16 July 2024). Facial Region-based Ensembling for Unsupervised Temporal Deepfake Localization [Paper presentation]. 2024 IEEE International Conference on Multimedia and Expo, Niagara Falls, Canada. doi:10.1109/ICME57554.2024.10688329
Peer reviewed

NGUYEN, V. D., MEJRI, N., SINGH, I. P., KULESHOVA, P., ASTRID, M., KACEM, A., GHORBEL, E., & AOUADA, D. (2024). LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detection. In LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detection (pp. 17395-17405). Seattle, WA, USA, Unknown/unspecified: The IEEE/CVF.
Editorial reviewed

SINGH, I. P., MEJRI, N., NGUYEN, V. D., Ghorbel, E., & AOUADA, D. (2023). Multi-label Deepfake Classification. IEEE Workshop on Multimedia Signal Processing. doi:10.1109/MMSP59012.2023.10337658
Peer reviewed

MEJRI, N., GHORBEL, E., & AOUADA, D. (2023). UNTAG: Learning Generic Features for Unsupervised Type-Agnostic Deepfake Detection. IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings. doi:10.1109/ICASSP49357.2023.10095983
Peer reviewed

MEJRI, N., PAPADOPOULOS, K., & AOUADA, D. (2021). Leveraging High-Frequency Components for Deepfake Detection. IEEE Workshop on Multimedia Signal Processing. doi:10.1109/MMSP53017.2021.9733606
Peer reviewed

MEJRI, N. (2021). Face-swap Deepfake Detection Using High-frequency Components [Bachelor/master dissertation, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/48065

MEJRI, N., DUPONT, E., & Da Costa, G. (2020). Energy-aware scheduling of malleable HPC applications using a Particle Swarm optimised greedy algorithm. Sustainable Computing: Informatics and Systems. doi:10.1016/j.suscom.2020.100447
Peer reviewed

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