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ASTRID Marcella

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

ORCID
0000-0003-1432-6661
Main Referenced Co-authors
AOUADA, Djamila  (5)
GHORBEL, Enjie  (3)
Lee, Seung-Ik (3)
Zaheer, Muhammad Zaigham (2)
JAMROZIK, Michele Lynn  (1)
Main Referenced Keywords
augmentation (3); Anomaly detection (1); audio deepfake detector (1); audio-visual (1); autonomous surveillance (1);
Main Referenced Unit & Research Centers
ULHPC - University of Luxembourg: High Performance Computing (3)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > CVI² - Computer Vision Imaging & Machine Intelligence (1)
Main Referenced Disciplines
Computer science (7)
Engineering, computing & technology: Multidisciplinary, general & others (1)
Space science, astronomy & astrophysics (1)

Publications (total 7)

The most downloaded
56 downloads
SHNEIDER, C., SINHA, N., JAMROZIK, M. L., ASTRID, M., ROSTAMI ABENDANSARI, P., KACEM, A., SHABAYEK, A. E. R., & AOUADA, D. (19 April 2023). Compression of Deep Neural Networks for Space Autonomous Systems [Poster presentation]. Luxembourg Space Resources Week 2023, Luxembourg, Luxembourg. doi:10.5281/zenodo.7931156 https://hdl.handle.net/10993/56045

The most cited

7 citations (Scopus®)

Zaheer, M. Z., Mahmood, A., ASTRID, M., & Lee, S.-I. (2023). Clustering Aided Weakly Supervised Training to Detect Anomalous Events in Surveillance Videos. IEEE Transactions on Neural Networks and Learning Systems. doi:10.1109/TNNLS.2023.3274611 https://hdl.handle.net/10993/55901

ASTRID, M., GHORBEL, E., & AOUADA, D. (October 2024). Statistics-aware Audio-visual Deepfake Detector [Paper presentation]. IEEE International Conference on Image Processing (ICIP 2024), Abu Dhabi, United Arab Emirates.
Peer reviewed

ASTRID, M., GHORBEL, E., & AOUADA, D. (August 2024). Targeted Augmented Data for Audio Deepfake Detection [Paper presentation]. 32nd European Signal Processing Conference (EUSIPCO 2024), Lyon, France.
Peer reviewed

ASTRID, M., Zaheer, M. Z., AOUADA, D., & Lee, S.-I. (2024). Exploiting autoencoder’s weakness to generate pseudo anomalies. Neural Computing and Applications. doi:10.1007/s00521-024-09790-z
Peer Reviewed verified by ORBi

ASTRID, M., GHORBEL, E., & AOUADA, D. (2024). Detecting Audio-Visual Deepfakes with Fine-Grained Inconsistencies [Paper presentation]. British Machine Vision Conference, Glasgow, United Kingdom.
Peer reviewed

ASTRID, M., & Lee, S.-I. (29 October 2023). Assembling Three One-Camera Images for Three-Camera Intersection Classification. ETRI Journal, 45 (5), 862-873. doi:10.4218/etrij.2023-0100
Peer Reviewed verified by ORBi

SHNEIDER, C., SINHA, N., JAMROZIK, M. L., ASTRID, M., ROSTAMI ABENDANSARI, P., KACEM, A., SHABAYEK, A. E. R., & AOUADA, D. (19 April 2023). Compression of Deep Neural Networks for Space Autonomous Systems [Poster presentation]. Luxembourg Space Resources Week 2023, Luxembourg, Luxembourg. doi:10.5281/zenodo.7931156

Zaheer, M. Z., Mahmood, A., ASTRID, M., & Lee, S.-I. (2023). Clustering Aided Weakly Supervised Training to Detect Anomalous Events in Surveillance Videos. IEEE Transactions on Neural Networks and Learning Systems. doi:10.1109/TNNLS.2023.3274611
Peer Reviewed verified by ORBi

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