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AOUADA Djamila

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

ORCID
0000-0002-7576-2064
Main Referenced Co-authors
OTTERSTEN, Björn  (71)
SHABAYEK, Abd El Rahman  (31)
GHORBEL, Enjie  (26)
KACEM, Anis  (25)
Mirbach, Bruno (20)
Main Referenced Keywords
Computer Science - Computer Vision and Pattern Recognition (10); Deep Learning (10); Computer Vision (7); Artificial Intelligence (5); Computer Vision and Pattern Recognition (4);
Main Referenced Unit & Research Centers
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SIGCOM (23)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > CVI² - Computer Vision Imaging & Machine Intelligence (13)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Computer Vision Imaging & Machine Intelligence (CVI²) (10)
ULHPC - University of Luxembourg: High Performance Computing (6)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) (2)
Main Referenced Disciplines
Computer science (133)
Electrical & electronics engineering (23)
Engineering, computing & technology: Multidisciplinary, general & others (7)
Aerospace & aeronautics engineering (4)
Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others (2)

Publications (total 153)

The most downloaded
2493 downloads
Correa Bahnsen, A., AOUADA, D., Stojanovic, A., & OTTERSTEN, B. (2015). Detecting Credit Card Fraud using Periodic Features. In IEEE International Conference on Machine Learning and Applications. https://hdl.handle.net/10993/24022

The most cited

325 citations (OpenAlex)

Correa Bahnsen, A., AOUADA, D., Stojanovic, A., & OTTERSTEN, B. (2016). Feature Engineering Strategies for Credit Card Fraud Detection. Expert Systems with Applications, 51, 134–142. doi:10.1016/j.eswa.2015.12.030 https://hdl.handle.net/10993/24073

ASTRID, M., GHORBEL, E., & AOUADA, D. (2025). Audio-Visual Deepfake Detection With Local Temporal Inconsistencies. IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings.
Peer reviewed

SHABAYEK, A. E. R., RATHINAM, A., RUTHVEN, M., AOUADA, D., & Amietszajew, T. (February 2025). AI-enabled thermal monitoring of commercial (PHEV) Li-ion pouch cells with Feature-Adapted Unsupervised Anomaly Detection. Journal of Power Sources, 629, 235982. doi:10.1016/j.jpowsour.2024.235982
Peer Reviewed verified by ORBi

HERMARY, R., GAUDILLIERE, V., SHABAYEK, A. E. R., & AOUADA, D. (2025). Removing Geometric Bias in One-Class Anomaly Detection with Adaptive Feature Perturbation [Paper presentation]. WACV.
Peer reviewed

RATHINAM, A., PAULY, L., SHABAYEK, A. E. R., RHARBAOUI, W., KACEM, A., GAUDILLIERE, V., & AOUADA, D. (January 2025). Hybrid Attention for Robust RGB-T Pedestrian Detection in Real-World Conditions. IEEE Robotics and Automation Letters, 10 (1), 1-8. doi:10.1109/LRA.2024.3504296
Peer Reviewed verified by ORBi

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

SOSA MARTINEZ, J. A., Aloulou, M., RUKHOVICH, D., Sleimi, R., CHANGAIVAL, B., KACEM, A., & AOUADA, D. (27 November 2024). How Effective is Pre-training of Large Masked Autoencoders for Downstream Earth Observation Tasks? [Paper presentation]. The 35th British Machine Vision Conference, Glasgow, United Kingdom.
Editorial 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

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

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

SINGH, I. P., GHORBEL, E., OYEDOTUN, O., & AOUADA, D. (13 July 2024). Multi-label image classification using adaptive graph convolutional networks: From a single domain to multiple domains. Computer Vision and Image Understanding, 247, 104062. doi:10.1016/j.cviu.2024.104062
Peer Reviewed verified by ORBi

Sinha, A., Kawahara, J., Pakzad, A., Abhishek, K., RUTHVEN, M., GHORBEL, E., KACEM, A., AOUADA, D., & Hamarneh, G. (July 2024). DermSynth3D: Synthesis of in-the-wild annotated dermatology images. Medical Image Analysis, 95, 103145. doi:10.1016/j.media.2024.103145
Peer Reviewed verified by ORBi

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. doi:10.1109/CVPR52733.2024.01647
Editorial reviewed

RATHINAM, A., Qadadri, H., & AOUADA, D. (13 May 2024). SPADES: A Realistic Spacecraft Pose Estimation Dataset using Event Sensing [Paper presentation]. 2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan. doi:10.1109/icra57147.2024.10611231
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

SINHA, N., ROSTAMI ABENDANSARI, P., SHABAYEK, A. E. R., KACEM, A., & AOUADA, D. (April 2024). Multi-Objective Hardware Aware Neural Architecture Search using Hardware Cost Diversity [Paper presentation]. Conference on Computer Vision and Pattern Recognition (CVPR) Workshop 2024, Seattle, United States.
Peer reviewed

SINGH, I. P., GHORBEL, E., KACEM, A., RATHINAM, A., & AOUADA, D. (2024). Discriminator-free Unsupervised Domain Adaptation for Multi-label Image Classification. IEEE/CVF WACV.
Peer reviewed

SINHA, N., SHABAYEK, A. E. R., KACEM, A., ROSTAMI ABENDANSARI, P., SHNEIDER, C., & AOUADA, D. (2024). Hardware Aware Evolutionary Neural Architecture Search using Representation Similarity Metric. Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024. doi:10.1109/WACV57701.2024.00261
Peer reviewed

Sadil Khan, M., DUPONT, E. M. E., Aziz Ali, S., CHERENKOVA, K., KACEM, A., & AOUADA, D. (2024). CAD-SIGNet: CAD Language Inference from Point Clouds using Layer-wise Sketch Instance Guided Attention. In CAD-SIGNet: CAD Language Inference from Point Clouds using Layer-wise Sketch Instance Guided Attention. IEEE.
Peer reviewed

DUPONT, E. M. E., CHERENKOVA, K., MALLIS, D., Gusev, G., KACEM, A., & AOUADA, D. (2024). TransCAD: A Hierarchical Transformer for CAD Sequence Inference from Point Clouds [Paper presentation]. ECCV'24.
Peer reviewed

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

CHERENKOVA, K., DUPONT, E. M. E., KACEM, A., Gleb Gusev, & AOUADA, D. (2024). SpelsNet: Surface Primitive Elements Segmentation by B-Rep Graph Structure Supervision [Paper presentation]. The Thirty-eighth Annual Conference on Neural Information Processing Systems.
Peer reviewed

PAULY, L., RHARBAOUI, W., SHNEIDER, C., RATHINAM, A., GAUDILLIERE, V., & AOUADA, D. (November 2023). A survey on deep learning-based monocular spacecraft pose estimation: Current state, limitations and prospects. Acta Astronautica, 212, 339-360. doi:10.1016/j.actaastro.2023.08.001
Peer Reviewed verified by ORBi

MALLIS, D., ALI, S. A., DUPONT, E., Cherenkova, K., KARADENIZ, A. S., KHAN, M. S., KACEM, A., Gleb, G., & AOUADA, D. (2023). SHARP Challenge 2023: Solving CAD History and pArameters Recovery from Point clouds and 3D scans. Overview, Datasets, Metrics, and Baselines. International Conference on Computer Vision Workshops. doi:10.1109/ICCVW60793.2023.00194
Peer reviewed

GAUDILLIERE, V., PAULY, L., RATHINAM, A., Garcia Sanchez, A., MOHAMED ALI, M. A., & AOUADA, D. (2023). 3D-Aware Object Localization using Gaussian Implicit Occupancy Function. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE. doi:10.1109/IROS55552.2023.10342399
Peer 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

SHNEIDER, C., ROSTAMI ABENDANSARI, P., KACEM, A., SINHA, N., SHABAYEK, A. E. R., & AOUADA, D. (19 July 2023). Impact of Disentanglement on Pruning Neural Networks [Paper presentation]. International Symposium on Computational Sensing (ISCS23), Luxembourg, Luxembourg. doi:10.48550/arXiv.2307.09994

CHERENKOVA, K., DUPONT, E. M. E., KACEM, A., Arzhannikov, I., Gusev, G., & AOUADA, D. (2023). SepicNet: Sharp Edges Recovery by Parametric Inference of Curves in 3D Shapes. In Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023. IEEE Computer Society. doi:10.1109/CVPRW59228.2023.00273
Peer reviewed

SHNEIDER, C., ROSTAMI ABENDANSARI, P., KACEM, A., SINHA, N., SHABAYEK, A. E. R., & AOUADA, D. (20 June 2023). Impact of Disentanglement on Pruning Neural Networks [Poster presentation]. International Symposium on Computational Sensing (ISCS23), Luxembourg, Luxembourg. doi:10.5281/zenodo.8060029

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

JAMROZIK, M. L., GAUDILLIERE, V., MOHAMED ALI, M. A., & AOUADA, D. (2023). Space Debris: Are Deep Learning-based Image Enhancements part of the Solution? Proceedings International Symposium on Computational Sensing.
Peer reviewed

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

MOHAMED ALI, M. A.* , GAUDILLIERE, V., & AOUADA, D. (2023). Self-Supervised Learning for Place Representation Generalization across Appearance Changes. Machine Vision and Applications. doi:10.1109/WACV57701.2024.00728
Peer Reviewed verified by ORBi

DUPONT, E., SINGH, I. P., Fuentes, L., ALI, S. A., KACEM, A., GHORBEL, E., & AOUADA, D. (2023). You Can Dance! Generating Music-Conditioned Dances on Real 3D Scans. Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2023, Volume 4: VISAPP. doi:10.5220/0011790900003417
Peer reviewed

Olivares-Mendez, M., Yalç\ina, B. C. C., Makhdoomia, M. R., Muralidharana, V., Bokala, Z., Del Castillob, M. O., Gaudilliereb, V., Paulyb, L., Borguec, O., Alandihallajc, M., THOEMEL, J., SKRZYPCZYK, E., RATHINAM, A., BARAD, K. R., SHABAYEK, A. E. R., HEIN, A., AOUADA, D., & Martinez, C. (2023). Establishing a Multi-Functional Space Operations Emulation Facility: Insights from the Zero-G Lab [Paper presentation]. Internal. doi:10.2139/ssrn.4602588

Olivares-Mendez, M., MAKHDOOMI, M. R., YALCIN, B. C., BOKAL, Z., MURALIDHARAN, V., Ortiz Del Castillo, M., GAUDILLIERE, V., PAULY, L., BORGUE, O., ALANDIHALLAJ, M., THOEMEL, J., SKRZYPCZYK, E., RATHINAM, A., BARAD, K. R., SHABAYEK, A. E. R., HEIN, A., AOUADA, D., & Martinez, C. (2023). Zero-G Lab: A multi-purpose facility for emulating space operations. Journal of Space Safety Engineering, 10 (4), 509–521. doi:10.1016/j.jsse.2023.09.003
Peer Reviewed verified by ORBi

PAULY, L., Lynn Jamrozik, M., Ortiz Del Castillo, M., BORGUE, O., SINGH, I. P., MAKHDOOMI, M. R., CHRISTIDI-LOUMPASEFSKI, O.-O., GAUDILLIERE, V., MARTINEZ LUNA, C., RATHINAM, A., HEIN, A., OLIVARES MENDEZ, M. A., & AOUADA, D. (2023). Lessons from a Space Lab -- An Image Acquisition Perspective. International Journal of Aerospace Engineering, 2023, 1-16. doi:10.1155/2023/9944614
Peer Reviewed verified by ORBi

LORENTZ, J., HARTMANN, T., MOAWAD, A., FOUQUET, F., AOUADA, D., & LE TRAON, Y. (2022). CalcGraph: taming the high costs of deep learning using models. Software and Systems Modeling. doi:10.1007/s10270-022-01052-7
Peer Reviewed verified by ORBi

RATHINAM, A., GAUDILLIERE, V., PAULY, L., & AOUADA, D. (2022). Pose Estimation of a Known Texture-Less Space Target using Convolutional Neural Networks. In 73rd International Astronautical Congress, Paris 18-22 September 2022.

LORENTZ, J., Hartmann, T., Moawad, A., & AOUADA, D. (2022). Profiling the real world potential of neural network compression. In 2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS), Barcelona 1-3 August 2022. IEEE. doi:10.1109/COINS54846.2022.9854973
Peer reviewed

KACEM, A., cherenkova, K., & AOUADA, D. (28 May 2022). Disentangled Face Identity Representationsfor Joint 3D Face Recognition and Neutralisation [Poster presentation]. International Conference on Virtual Reality. doi:10.1109/ICVR55215.2022.9848415
Peer reviewed

Papadopoulos, K., KACEM, A., Shabayek, A., & AOUADA, D. (2022). Face-GCN: A Graph Convolutional Network for 3D Dynamic Face Recognition. 2022 8th International Conference on Virtual Reality. doi:10.1109/ICVR55215.2022.9847930
Peer reviewed

OYEDOTUN, O., & AOUADA, D. (22 May 2022). A CLOSER LOOK AT AUTOENCODERS FOR UNSUPERVISED ANOMALY DETECTION [Poster presentation]. 2022 IEEE International Conference on Acoustics, Speech, & Signal Processing (ICASSP).

SINGH, I. P., OYEDOTUN, O., GHORBEL, E., & AOUADA, D. (2022). IML-GCN: Improved Multi-Label Graph Convolutional Network for Efficient yet Precise Image Classification. AAAI-22 Workshop Program-Deep Learning on Graphs: Methods and Applications.
Peer reviewed

SINGH, I. P., GHORBEL, E., OYEDOTUN, O., & AOUADA, D. (2022). MULTI LABEL IMAGE CLASSIFICATION USING ADAPTIVE GRAPH CONVOLUTIONAL NETWORKS (ML-AGCN). IEEE International Conference on Image Processing.
Peer reviewed

KARADENIZ, A. S., ALI, S. A., KACEM, A., DUPONT, E., & AOUADA, D. (2022). TSCom-Net: Coarse-to-Fine 3D Textured Shape Completion Network. In A. S. KARADENIZ, S. A. ALI, A. KACEM, E. DUPONT, ... D. AOUADA, TSCom-Net: Coarse-to-Fine 3D Textured Shape Completion Network.
Peer reviewed

MOHAMED ALI, M. A., GAUDILLIERE, V., ORTIZ DEL CASTILLO, M., AL ISMAEIL, K., & AOUADA, D. (2022). Leveraging Equivariant Features for Absolute Pose Regression. IEEE Conference on Computer Vision and Pattern Recognition.
Peer reviewed

MOHAMED ALI, M. A., RATHINAM, A., GAUDILLIERE, V., ORTIZ DEL CASTILLO, M., & AOUADA, D. (2022). CubeSat-CDT: A Cross-Domain Dataset for 6-DoF Trajectory Estimation of a Symmetric Spacecraft. Proceedings of the 17th European Conference on Computer Vision Workshops (ECCVW 2022).
Peer reviewed

JAMROZIK, M. L., GAUDILLIERE, V., MOHAMED ALI, M. A., & AOUADA, D. (2022). Image Enhancement for Space Surveillance and Tracking. In M. L. JAMROZIK, V. GAUDILLIERE, M. A. Musallam, ... D. AOUADA, Proceedings of the 73rd International Astronautical Congress. Paris, France: International Astronautical Federation.

DUPONT, E. M. E., CHERENKOVA, K., KACEM, A., ALI, S. A., Arzhannikov, I., Gusev, G., & AOUADA, D. (2022). CADOps-Net: Jointly Learning CAD Operation Types and Steps from Boundary-Representations. In Proceedings - 2022 International Conference on 3D Vision, 3DV 2022. Institute of Electrical and Electronics Engineers Inc. doi:10.1109/3DV57658.2022.00024
Peer reviewed

OYEDOTUN, O., Al Ismaeil, K., & AOUADA, D. (2021). Why is Everyone Training Very Deep Neural Network with Skip Connections? IEEE Transactions on Neural Networks and Learning Systems. doi:10.1109/TNNLS.2021.3131813
Peer Reviewed verified by ORBi

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

MOHAMED ALI, M. A., ORTIZ DEL CASTILLO, M., AL ISMAEIL, K., Perez, M., & AOUADA, D. (2021). Leveraging Temporal Information for 3D Trajectory Estimation of Space Objects. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops.
Peer reviewed

ORTIZ DEL CASTILLO, M., MOHAMED ALI, M. A., JAMROZIK, M. L., GAUDILLIERE, V., & AOUADA, D. (September 2021). Deep Learning-based Image Enhancement for Space Applications [Paper presentation]. ESA EO Φ-WEEK.

LORENTZ, J., Hartmann, T., Moawad, A., Fouquet, F., & AOUADA, D. (2021). Explaining Defect Detection with Saliency Maps. In 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26–29, 2021, Proceedings, Part II (pp. 506-518). Cham, Switzerland: Springer. doi:10.1007/978-3-030-79463-7_43
Peer reviewed

OYEDOTUN, O., AL ISMAEIL, K., & AOUADA, D. (2021). Training very deep neural networks: Rethinking the role of skip connections. Neurocomputing. doi:10.1016/j.neucom.2021.02.004
Peer Reviewed verified by ORBi

GARCIA SANCHEZ, A., MOHAMED ALI, M. A., GAUDILLIERE, V., GHORBEL, E., AL ISMAEIL, K., Perez, M., & AOUADA, D. (2021). LSPnet: A 2D Localization-oriented Spacecraft Pose Estimation Neural Network. Proceedings of Conference on Computer Vision and Pattern Recognition Workshops, 2048-2056. doi:10.1109/CVPRW53098.2021.00233
Peer reviewed

SHABAYEK, A. E. R., & AOUADA, D. (2021). Dense and Sparse 3D Deformation Signatures for 3D Dynamic Face Recognition. IEEE Access, 9, 38687-38705. doi:10.1109/ACCESS.2021.3064179
Peer Reviewed verified by ORBi

Perez, M., MOHAMED ALI, M. A., GARCIA SANCHEZ, A., GHORBEL, E., AL ISMAEIL, K., Le Henaff, P., & AOUADA, D. (2021). Detection & Identification of On-Orbit Objects Using Machine Learning. European Conference on Space Debris, 8 (1).

MOHAMED ALI, M. A., GAUDILLIERE, V., GHORBEL, E., AL ISMAEIL, K., Perez, M., Poucet, M., & AOUADA, D. (2021). SPACECRAFT RECOGNITION LEVERAGING KNOWLEDGE OF SPACE ENVIRONMENT: SIMULATOR, DATASET, COMPETITION DESIGN, AND ANALYSIS. 2021 IEEE International Conference on Image Processing (ICIP).
Peer reviewed

PAPADOPOULOS, K., GHORBEL, E., AOUADA, D., & OTTERSTEN, B. (2021). Vertex Feature Encoding and Hierarchical Temporal Modeling in a Spatio-Temporal Graph Convolutional Network for Action Recognition. In International Conference on Pattern Recognition, Milan 10-15 January 2021. doi:10.1109/ICPR48806.2021.9413189
Peer reviewed

OYEDOTUN, O., SHABAYEK, A. E. R., AOUADA, D., & OTTERSTEN, B. (2021). Revisiting the Training of Very Deep Neural Networks without Skip Connections [Poster presentation]. IEEE 2020 International Conference on Pattern Recognition (ICPR). doi:10.1109/ICPR48806.2021.9412508

OYEDOTUN, O., & AOUADA, D. (18 November 2020). Why do Deep Neural Networks with Skip Connections and Concatenated Hidden Representations Work? [Poster presentation]. The 27th International Conference on Neural Information Processing (ICONIP2020).

GHORBEL, E., BAPTISTA, R., SHABAYEK, A. E. R., AOUADA, D., Gorostiza Oramaeche, M., Orcajo Lago, J., & Ortiz Fernandez, L. (2020). Home-based rehabilitation system for strokesurvivors: a clinical evaluation. Journal of Medical Systems. doi:10.1007/s10916-020-01661-z
Peer reviewed

OYEDOTUN, O., SHABAYEK, A. E. R., AOUADA, D., & OTTERSTEN, B. (2020). Improved Highway Network Block for Training Very Deep Neural Networks. IEEE Access. doi:10.1109/ACCESS.2020.3026423
Peer Reviewed verified by ORBi

CHERENKOVA, K., AOUADA, D., & Gusev, G. (October 2020). PVDeConv: Point-Voxel Deconvolution for Autoencoding CAD Construction in 3D [Paper presentation]. IEEE International Conference on Image Processing.

SHABAYEK, A. E. R., AOUADA, D., CHERENKOVA, K., & Gusev, G. (2020). 3D SPARSE DEFORMATION SIGNATURE FOR DYNAMIC FACE RECOGNITION. In 27th IEEE International Conference on Image Processing (ICIP 2020), Abu Dhabi 25-28 October 2020.
Peer reviewed

OYEDOTUN, O., SHABAYEK, A. E. R., AOUADA, D., & OTTERSTEN, B. (2020). Deep network compression with teacher latent subspace learning and LASSO. Applied Intelligence. doi:10.1007/s10489-020-01858-2
Peer Reviewed verified by ORBi

SAINT, A. F. A., KACEM, A., CHERENKOVA, K., & AOUADA, D. (23 August 2020). 3DBooSTeR: 3D Body Shape and Texture Recovery [Paper presentation]. SHARP workshop, ECCV 2020.

SAINT, A. F. A., KACEM, A., CHERENKOVA, K., PAPADOPOULOS, K., Chibane, J., Pons-Moll, G., Gusev, G., Foffi, D., AOUADA, D., & OTTERSTEN, B. (23 August 2020). SHARP 2020: The 1st Shape Recovery from Partial Textured 3D Scans Challenge Results [Paper presentation]. SHARP workshop, ECCV 2020.

OYEDOTUN, O., SHABAYEK, A. E. R., AOUADA, D., & OTTERSTEN, B. (2020). GOING DEEPER WITH NEURAL NETWORKS WITHOUT SKIP CONNECTIONS. In IEEE International Conference on Image Processing (ICIP 2020), Abu Dhabi, UAE, Oct 25–28, 2020.
Peer reviewed

SHABAYEK, A. E. R., AOUADA, D., CHERENKOVA, K., Gusev, G., & OTTERSTEN, B. (2020). 3D DEFORMATION SIGNATURE FOR DYNAMIC FACE RECOGNITION. In 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), Barcelona 4-8 May 2020.
Peer reviewed

OYEDOTUN, O., AOUADA, D., & OTTERSTEN, B. (2020). Structured Compression of Deep Neural Networks with Debiased Elastic Group LASSO. In IEEE 2020 Winter Conference on Applications of Computer Vision (WACV 20), Aspen, Colorado, US, March 2–5, 2020.
Peer reviewed

SHABAYEK, A. E. R., AOUADA, D., CHERENKOVA, K., & Gusev, G. (2020). Towards Automatic CAD Modeling from 3D Scan Sketch based Representation. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020), GRAPP (pp. 392-398).
Peer reviewed

BAPTISTA, R., SAINT, A. F. A., AL ISMAEIL, K., & AOUADA, D. (2020). Towards Generalization of 3D Human Pose Estimation In The Wild. In International Conference on Pattern Recognition (ICPR) Workshop on 3D Human Understanding, Milan 10-15 January 2021.
Peer reviewed

PAPADOPOULOS, K., GHORBEL, E., OYEDOTUN, O., AOUADA, D., & OTTERSTEN, B. (2020). DeepVI: A Novel Framework for Learning Deep View-Invariant Human Action Representations using a Single RGB Camera. In IEEE International Conference on Automatic Face and Gesture Recognition, Buenos Aires 18-22 May 2020.
Peer reviewed

KACEM, A., BEN ABDESSALEM, H., CHERENKOVA, K., & AOUADA, D. (2020). Space-Time Triplet Loss Network for Dynamic 3D Face Verification [Paper presentation]. Workshop on 3D Human Understanding, ICPR 2020.

GHORBEL, E., DEMISSE, G., AOUADA, D., & OTTERSTEN, B. (2020). Fast Adaptive Reparametrization (FAR) with Application to Human Action Recognition. IEEE Signal Processing Letters. doi:10.1109/LSP.2020.2983901
Peer Reviewed verified by ORBi

Adel Musallam, M., BAPTISTA, R., AL ISMAEIL, K., & AOUADA, D. (2019). Temporal 3D Human Pose Estimation for Action Recognition from Arbitrary Viewpoints. In 6th Annual Conf. on Computational Science & Computational Intelligence, Las Vegas 5-7 December 2019. Conference Publishing Services.
Peer reviewed

SAINT, A. F. A., SHABAYEK, A. E. R., CHERENKOVA, K., Gusev, G., AOUADA, D., & OTTERSTEN, B. (2019). BODYFITR: Robust Automatic 3D Human Body Fitting. In Proceedings of the 2019 IEEE International Conference on Image Processing (ICIP). IEEE. doi:10.1109/ICIP.2019.8803819
Peer reviewed

OYEDOTUN, O., AOUADA, D., & OTTERSTEN, B. (14 May 2019). Learning to Fuse Latent Representations for Multimodal Data [Poster presentation]. 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, United Kingdom.

BAPTISTA, R., GHORBEL, E., PAPADOPOULOS, K., Demisse, G., AOUADA, D., & OTTERSTEN, B. (2019). VIEW-INVARIANT ACTION RECOGNITION FROM RGB DATA VIA 3D POSE ESTIMATION. In IEEE International Conference on Acoustics, Speech and Signal Processing, Brighton, UK, 12–17 May 2019.
Peer reviewed

GHORBEL, E., PAPADOPOULOS, K., BAPTISTA, R., Pathak, H., Demisse, G., AOUADA, D., & OTTERSTEN, B. (2019). A View-invariant Framework for Fast Skeleton-based Action Recognition Using a Single RGB Camera. In 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Prague, 25-27 February 2018.
Peer reviewed

PAPADOPOULOS, K., DEMISSE, G., GHORBEL, E., Antunes, M., AOUADA, D., & OTTERSTEN, B. (2019). Localized Trajectories for 2D and 3D Action Recognition. Sensors. doi:10.3390/s19163503
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BAPTISTA, R., GHORBEL, E., SHABAYEK, A. E. R., Moissenet, F., AOUADA, D., Douchet, A., André, M., Pager, J., & Bouilland, S. (2019). Home Self-Training: Visual Feedback for Assisting Physical Activity for Stroke Survivors. Computer Methods and Programs in Biomedicine. doi:10.1016/j.cmpb.2019.04.019
Peer reviewed

PAPADOPOULOS, K., GHORBEL, E., BAPTISTA, R., AOUADA, D., & OTTERSTEN, B. (2019). Two-stage RGB-based Action Detection using Augmented 3D Poses. In 18th International Conference on Computer Analysis of Images and Patterns SALERNO, 3-5 SEPTEMBER, 2019.
Peer reviewed

BAPTISTA, R., DEMISSE, G., AOUADA, D., & OTTERSTEN, B. (2018). Deformation-Based Abnormal Motion Detection using 3D Skeletons. In IEEE International Conference on Image Processing Theory, Tools and Applications (IPTA).
Peer reviewed

OYEDOTUN, O., SHABAYEK, A. E. R., AOUADA, D., & OTTERSTEN, B. (2018). Highway Network Block with Gates Constraints for Training Very Deep Networks. In 2018 IEEE International Conference on Computer Vision and Pattern Recognition Workshop, June 18-22, 2018.
Peer reviewed

DEMISSE, G., PAPADOPOULOS, K., AOUADA, D., & OTTERSTEN, B. (2018). Pose Encoding for Robust Skeleton-Based Action Recognition. In CVPRW: Visual Understanding of Humans in Crowd Scene, Salt Lake City, Utah, June 18-22, 2018.
Peer reviewed

BAPTISTA, R., GHORBEL, E., SHABAYEK, A. E. R., AOUADA, D., & OTTERSTEN, B. (2018). Key-Skeleton Based Feedback Tool for Assisting Physical Activity. In 2018 Zooming Innovation in Consumer Electronics International Conference (ZINC), 30-31 May 2018.
Peer reviewed

OYEDOTUN, O., SHABAYEK, A. E. R., AOUADA, D., & OTTERSTEN, B. (2018). IMPROVING THE CAPACITY OF VERY DEEP NETWORKS WITH MAXOUT UNITS. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing.
Peer reviewed

BAPTISTA, R., Antunes, M., AOUADA, D., & OTTERSTEN, B. (2018). Anticipating Suspicious Actions using a Small Dataset of Action Templates. In 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP).
Peer reviewed

Afzal, H., AOUADA, D., Mirbach, B., & OTTERSTEN, B. (2018). Full 3D Reconstruction of Non-Rigidly Deforming Objects. ACM Transactions on Multimedia Computing, Communications, and Applications. doi:10.1145/3177756
Peer reviewed

PAPADOPOULOS, K., Antunes, M., AOUADA, D., & OTTERSTEN, B. (2018). A Revisit of Action Detection using Improved Trajectories. In IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Alberta, Canada, 15–20 April 2018.
Peer reviewed

DEMISSE, G., AOUADA, D., & OTTERSTEN, B. (2018). Deformation Based 3D Facial Expression Representation. ACM Transactions on Multimedia Computing, Communications, and Applications. doi:10.1145/3176649
Peer reviewed

SAINT, A. F. A., AHMED, E., SHABAYEK, A. E. R., CHERENKOVA, K., Gusev, G., AOUADA, D., & OTTERSTEN, B. (2018). 3DBodyTex: Textured 3D Body Dataset. In 2018 Sixth International Conference on 3D Vision (3DV 2018).
Peer reviewed

SAINT, A. F. A., SHABAYEK, A. E. R., AOUADA, D., OTTERSTEN, B., Cherenkova, K., & Gusev, G. (2017). Towards Automatic Human Body Model Fitting to a 3D Scan. In N. D'APUZZO (Ed.), Proceedings of 3DBODY.TECH 2017 - 8th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Montreal QC, Canada, 11-12 Oct. 2017 (pp. 274-280). Ascona, Switzerland: Hometrica Consulting. doi:10.15221/17.274
Peer reviewed

OYEDOTUN, O., DEMISSE, G., SHABAYEK, A. E. R., AOUADA, D., & OTTERSTEN, B. (2017). Facial Expression Recognition via Joint Deep Learning of RGB-Depth Map Latent Representations. In 2017 IEEE International Conference on Computer Vision Workshop (ICCVW). doi:10.1109/ICCVW.2017.374
Peer reviewed

OYEDOTUN, O., SHABAYEK, A. E. R., AOUADA, D., & OTTERSTEN, B. (2017). Training Very Deep Networks via Residual Learning with Stochastic Input Shortcut Connections. In 24th International Conference on Neural Information Processing, Guangzhou, China, November 14–18, 2017.
Peer reviewed

PAPADOPOULOS, K., GONCALVES ALMEIDA ANTUNES, M., AOUADA, D., & OTTERSTEN, B. (2017). Enhanced Trajectory-based Action Recognition using Human Pose. In IEEE International Conference on Image Processing, Beijing 17-20 Spetember 2017.
Peer reviewed

BAPTISTA, R., GONCALVES ALMEIDA ANTUNES, M., AOUADA, D., & OTTERSTEN, B. (2017). Video-Based Feedback for Assisting Physical Activity. In 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP).
Peer reviewed

SHABAYEK, A. E. R., AOUADA, D., SAINT, A. F. A., & OTTERSTEN, B. (2017). DEFORMATION TRANSFER OF 3D HUMAN SHAPES AND POSES ON MANIFOLDS. In IEEE International Conference on Image Processing, Beijing 17-20 Spetember 2017.
Peer reviewed

BAPTISTA, R., Antunes, M., SHABAYEK, A. E. R., AOUADA, D., & OTTERSTEN, B. (2017). Flexible Feedback System for Posture Monitoring and Correction. In IEEE International Conference on Image Information Processing (ICIIP).
Peer reviewed

DEMISSE, G., AOUADA, D., & OTTERSTEN, B. (2017). Deformation Based Curved Shape Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence. doi:10.1109/TPAMI.2017.2711607
Peer Reviewed verified by ORBi

GONCALVES ALMEIDA ANTUNES, M., Barreto, J. P., AOUADA, D., & OTTERSTEN, B. (2017). Unsupervised Vanishing Point Detection and Camera Calibration from a Single Manhattan Image with Radial Distortion. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
Peer reviewed

Correa Bahnsen, A., Villegas, S., AOUADA, D., & OTTERSTEN, B. (2017). Fraud Detection by Stacking Cost-Sensitive Decision Trees. In Data Science for Cyber-Security (DSCS), London 25-27 September.
Peer reviewed

SHABAYEK, A. E. R., BAPTISTA, R., PAPADOPOULOS, K., Demisse, G., OYEDOTUN, O., Antunes, M., AOUADA, D., OTTERSTEN, B., Anastassova, M., Boukallel, M., Panëels, S., Randall, G., André, M., Douchet, A., Bouilland, S., & Ortiz Fernandez, L. (2017). STARR - Decision SupporT and self-mAnagement system for stRoke survivoRs Vision based Rehabilitation System. In European Project Space on Networks, Systems and Technologies (pp. 69-80). SciTePress. doi:10.5220/0007902400690080

Al Ismaeil, K., AOUADA, D., Solignac, T., Mirbach, B., & OTTERSTEN, B. (27 October 2016). Real-Time Enhancement of Dynamic Depth Videos with Non-Rigid Deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39 (10), 2045-2059. doi:10.1109/TPAMI.2016.2622698
Peer Reviewed verified by ORBi

DEMISSE, G., AOUADA, D., & OTTERSTEN, B. (2016). Similarity Metric For Curved Shapes In Euclidean Space. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016. doi:10.1109/CVPR.2016.545
Peer reviewed

Correa Bahnsen, A., AOUADA, D., Stojanovic, A., & OTTERSTEN, B. (2016). Feature Engineering Strategies for Credit Card Fraud Detection. Expert Systems with Applications, 51, 134–142. doi:10.1016/j.eswa.2015.12.030
Peer reviewed

Rocco, I., GONCALVES ALMEIDA ANTUNES, M., AOUADA, D., & OTTERSTEN, B. (2016). RGB-D and Thermal Sensor Fusion. In 11th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP).
Peer reviewed

GONCALVES ALMEIDA ANTUNES, M., AOUADA, D., & OTTERSTEN, B. (2016). A Revisit to Human Action Recognition from Depth Sequences: Guided SVM-Sampling for Joint Selection. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2016.
Peer reviewed

GONCALVES ALMEIDA ANTUNES, M., BAPTISTA, R., DEMISSE, G., AOUADA, D., & OTTERSTEN, B. (2016). Visual and human-interpretable feedback for assisting physical activity. In European Conference on Computer Vision (ECCV) Workshop on Assistive Computer Vision and Robotics Amsterdam.
Peer reviewed

Al Ismaeil, K., AOUADA, D., Mirbach, B., & OTTERSTEN, B. (2016). Enhancement of Dynamic Depth Scenes by Upsampling for Precise Super-Resolution (UP-SR). Computer Vision and Image Understanding. doi:10.1016/j.cviu.2016.04.006
Peer reviewed

Correa Bahnsen, A., AOUADA, D., Stojanovic, A., & OTTERSTEN, B. (2015). Detecting Credit Card Fraud using Periodic Features. In IEEE International Conference on Machine Learning and Applications.
Peer reviewed

CORREA BAHNSEN, A., AOUADA, D., & OTTERSTEN, B. (01 November 2015). Example-Dependent Cost-Sensitive Decision Trees. Expert Systems with Applications, 42 (19), 6609-6619. doi:10.1016/j.eswa.2015.04.042
Peer reviewed

GARCIA BECERRO, F., AOUADA, D., Mirbach, B., Solignac, T., & OTTERSTEN, B. (September 2015). Unified Multi-Lateral Filter for Real-Time Depth Map Enhancement. Image and Vision Computing, 41, 26-42. doi:10.1016/j.imavis.2015.06.008
Peer Reviewed verified by ORBi

CORREA BAHNSEN, A., AOUADA, D., & OTTERSTEN, B. (13 June 2015). A novel cost-sensitive framework for customer churn predictive modeling. Decision Analytics, 2 (5). doi:10.1186/s40165-015-0014-6
Peer reviewed

AL ISMAEIL, K., AOUADA, D., Solignac, T., Mirbach, B., & OTTERSTEN, B. (2015). Real-Time Non-Rigid Multi-Frame Depth Video Super-Resolution. In IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'15), (Best paper award).
Peer reviewed

AOUADA, D., AL ISMAEIL, K., & OTTERSTEN, B. (2015). Patch-based Statistical Performance Analysis of Upsampling for Precise Super–Resolution. In 11th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP'15).
Peer reviewed

DEMISSE, G., AOUADA, D., & OTTERSTEN, B. (2015). Template-Based Statistical Shape Modelling on Deformation Space. In 22nd IEEE International Conference on Image Processing.
Peer reviewed

AFZAL, H., AOUADA, D., Destelle, F., Mirbach, B., & OTTERSTEN, B. (2015). View-Independent Enhanced 3D Reconstruction of Non-Rigidly Deforming Objects. In 16th International Conference on Computer Analysis of Images and Patterns. doi:10.1007/978-3-319-23117-4_61
Peer reviewed

Bahnsen, A. C., AOUADA, D., & OTTERSTEN, B. (2015). Ensemble of Example-Dependent Cost-Sensitive Decision Trees. arXiv preprint arXiv:1505.04637. doi:10.1016/j.eswa.2015.04.042
Peer reviewed

CORREA BAHNSEN, A., AOUADA, D., & OTTERSTEN, B. (2014). Example-Dependent Cost-Sensitive Logistic Regression for Credit Scoring. In 2014 13th International Conference on Machine Learning and Applications (pp. 263-269). Detroit, United States: IEEE. doi:10.1109/ICMLA.2014.48
Peer reviewed

AOUADA, D., & KHADER, D. (2014). SPN2: Single-Sided Privacy Preserving Nearest Neighbor and its Application to Face Recognition. In 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS'14). doi:10.1109/AVSS.2014.6918640
Peer reviewed

CORREA BAHNSEN, A., STOJANOVIC, A., AOUADA, D., & OTTERSTEN, B. (2014). Improving Credit Card Fraud Detection with Calibrated Probabilities. In Proceedings of the fourteenth SIAM International Conference on Data Mining, Philadelphia, Pennsylvania, USA, April 24-26, 2014 (pp. 677-685). Philadelphia, United States: Society for Industrial and Applied Mathematics.
Peer reviewed

AFZAL, H., AL ISMAEIL, K., AOUADA, D., Destelle, F. O., Mirbach, B., & OTTERSTEN, B. (2014). KinectDeform: Enhanced 3D Reconstruction of Non-Rigidly Deforming Objects. In Second International Conference on 3D Vision. Tokyo, Japan: IEEE Computer Society's Conference Publishing Services (CPS).
Peer reviewed

AOUADA, D., AL ISMAEIL, K., Kedir Idris, K., & OTTERSTEN, B. (2014). Surface UP-SR for an Improved Face Recognition Using Low Resolution Depth Cameras. In 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS'14).
Peer reviewed

AFZAL, H., AOUADA, D., Fofi, D., Mirbach, B., & OTTERSTEN, B. (2014). RGB-D Multi-View System Calibration for Full 3D Scene Reconstruction. In 22nd International Conference on Pattern Recognition (ICPR'14).
Peer reviewed

AL ISMAEIL, K., AOUADA, D., Mirbach, B., & OTTERSTEN, B. (2013). Dynamic Super Resolution of Depth Sequences with Non-Rigid Motions. In 20th International Conference on Image Processing. doi:10.1109/ICIP.2013.6738136
Peer reviewed

GARCIA BECERRO, F., AOUADA, D., Solignac, T., Mirbach, B., & OTTERSTEN, B. (2013). Real-time depth enhancement by fusion for RGB-D cameras. IET Computer Vision, 7 (5), 335 – 345. doi:10.1049/iet-cvi.2012.0289
Peer reviewed

AL ISMAEIL, K., AOUADA, D., Mirbach, B., & OTTERSTEN, B. (2013). Mutli-Frame Super-Resolution by Enhanced Shift & Add. In 8th International Symposium on Image and Signal Processing and Analysis.
Peer reviewed

AL ISMAEIL, K., AOUADA, D., Mirbach, B., & OTTERSTEN, B. (2013). Depth Super-Resolution by Enhanced Shift and Add. In Computer Analysis of Images and Patterns, 15th International Conference, CAIP 2013, York, UK, August 27-29, 2013, Proceedings, Part II (pp. 100-107). Springer Berlin Heidelberg. doi:10.1007/978-3-642-40246-3_13
Peer reviewed

CORREA BAHNSEN, A., STOJANOVIC, A., AOUADA, D., & OTTERSTEN, B. (2013). Cost Sensitive Credit Card Fraud Detection using Bayes Minimum Risk. In 12th International Conference on Machine Learning and Applications (pp. 333-338). IEEE Computer Society. doi:10.1109/ICMLA.2013.68
Peer reviewed

GARCIA BECERRO, F., AOUADA, D., ABDELLA, H. K., Solignac, T., Mirbach, B., & OTTERSTEN, B. (2012). Depth Enhancement by Fusion for Passive and Active Sensing. In Computer Vision – ECCV 2012. Workshops and Demonstrations (pp. 506-515). Springer Berlin Heidelberg.
Peer reviewed

GARCIA BECERRO, F., AOUADA, D., Mirbach, B., & OTTERSTEN, B. (2012). Spatio-Temporal ToF Data Enhancement by Fusion. In 19th IEEE International Conference on Image Processing (pp. 981 - 984).
Peer reviewed

GARCIA BECERRO, F., AOUADA, D., Mirbach, B., & OTTERSTEN, B. (2012). Real-Time Distance-Dependent Mapping for a Hybrid ToF Multi-Camera Rig. IEEE Journal of Selected Topics in Signal Processing, 6 (5), 1-12. doi:10.1109/JSTSP.2012.2207090
Peer Reviewed verified by ORBi

AL ISMAEIL, K., AOUADA, D., Mirbach, B., & OTTERSTEN, B. (2012). Bilateral Filter Evaluation Based on Exponential Kernels. In Pattern Recognition (ICPR), 2012 21st International Conference on (pp. 258 - 261). IEEE Xplore.
Peer reviewed

GARCIA BECERRO, F., AOUADA, D., Mirbach, B., Solignac, T., & OTTERSTEN, B. (2011). Real-Time Hybrid ToF Multi-Camera Rig Fusion System for Depth Map Enhancement. In 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (pp. 1-8).
Peer reviewed

GARCIA BECERRO, F., AOUADA, D., Mirbach, B., Solignac, T., & OTTERSTEN, B. (2011). A New Multi-Lateral Filter for Real-Time Depth Enhancement. In 8th IEEE International Conference on Advanced Video and Signal-Based Surveillance (pp. 42-47). doi:10.1109/AVSS.2011.6027291
Peer reviewed

GARCIA BECERRO, F., AOUADA, D., Mirbach, B., & OTTERSTEN, B. (2011). A New 1-D Colour Model and its Application to Image Filtering. In 2011 7th International Symposium on Image and Signal Processing and Analysis (ISPA) (pp. 134-138). IEEE Xplore.
Peer reviewed

GARCIA BECERRO, F., AOUADA, D., Mirbach, B., & OTTERSTEN, B. (2011). Spiral Colour Model: Reduction from 3-D to 2-D. In International Conference on Acoustics, Speech and Signal Processing (pp. 1305 - 1308). doi:10.1109/ICASSP.2011.5946651
Peer reviewed

Nagaraja, S., SCHAFFER, P., & AOUADA, D. (2011). Who Clicks There!: Anonymizing the Photographer in a Camera Saturated Society. In Workshop on Privacy in the Electronic Society (WPES) (pp. 13-22).
Peer reviewed

AOUADA, D., & Krim, H. (2010). Squigraphs for Fine and Compact Modeling of 3-D shapes. IEEE Transactions on Image Processing, 19, 306-321. doi:10.1109/TIP.2009.2034693
Peer Reviewed verified by ORBi

AOUADA, D., Baryshnikov, Y., & Krim, H. (2010). Mahalanobis-based Adaptive Nonlinear Dimension Reduction. In 20th International Conference on Pattern Recognition (pp. 742 - 745). IEEE Xplore.
Peer reviewed

AOUADA, D., & Krim, H. (2009). Meaningful 3D shape partitioning using Morse functions. In 2009 16th IEEE International Conference on Image Processing (pp. 417 - 420).
Peer reviewed

AOUADA, D., & Krim, H. (2009). Novel similarity invariant for space curves using turning angles and its application to object recognition. In IEEE International Conference on Acoustics, Speech and Signal Processing, 2009. ICASSP 2009 (pp. 1277 - 1280). doi:10.1109/ICASSP.2009.4959824
Peer reviewed

AOUADA, D., & Krim, H. (2008). 3D Object Recognition Using Fully Intrinsic Skeletal Graphs. In International Conference on Computational Imaging, 2008 (pp. 1 - 8). doi:10.1117/12.774868
Peer reviewed

AOUADA, D., Dreisigmeyer, D., & Krim, H. (2008). Geometric modeling of rigid and non-rigid 3D shapes using the global geodesic function. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08 (pp. 1-8). doi:10.1109/CVPRW.2008.4563075
Peer reviewed

Feng, S., AOUADA, D., Krim, H., & Kogan, I. (2007). 3D Mixed Invariant and its Application on Object Classification. In IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. ICASSP 2007 (pp. 461 - 464). doi:10.1109/ICASSP.2007.366716
Peer reviewed

AOUADA, D., Feng, S., & Krim, H. (2007). Statistical Analysis of the Global Geodesic Function for 3D Object Classification. In IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. ICASSP 2007 (pp. 645- 648). doi:10.1109/ICASSP.2007.365990
Peer reviewed

LORENTZ, J., Hartmann, T., Moawad, A., & AOUADA, D. (n.d.). Industrial defect detection on the edge with deep learning over scarcely labeled and extremely imbalanced data. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/54839.

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