| Feature engineering strategies for credit card fraud detection AC Bahnsen, D Aouada, A Stojanovic, B Ottersten Expert Systems with Applications 51, 134-142, 2016 | 459 | 2016 |
| Example-dependent cost-sensitive decision trees AC Bahnsen, D Aouada, B Ottersten Expert Systems with Applications 42 (19), 6609-6619, 2015 | 290 | 2015 |
| Cost sensitive credit card fraud detection using Bayes minimum risk AC Bahnsen, A Stojanovic, D Aouada, B Ottersten 2013 12th international conference on machine learning and applications 1 …, 2013 | 234 | 2013 |
| A survey on deep learning advances on different 3D data representations E Ahmed, A Saint, AER Shabayek, K Cherenkova, R Das, G Gusev, ... arXiv preprint arXiv:1808.01462, 2018 | 213 | 2018 |
| Example-dependent cost-sensitive logistic regression for credit scoring AC Bahnsen, D Aouada, B Ottersten 2014 13th International conference on machine learning and applications, 263-269, 2014 | 167 | 2014 |
| Improving credit card fraud detection with calibrated probabilities AC Bahnsen, A Stojanovic, D Aouada, B Ottersten Proceedings of the 2014 SIAM international conference on data mining, 677-685, 2014 | 113 | 2014 |
| A novel cost-sensitive framework for customer churn predictive modeling AC Bahnsen, D Aouada, B Ottersten Decision Analytics 2, 1-15, 2015 | 70 | 2015 |
| Vertex feature encoding and hierarchical temporal modeling in a spatial-temporal graph convolutional network for action recognition K Papadopoulos, E Ghorbel, D Aouada, B Ottersten arXiv preprint arXiv:1912.09745, 2019 | 63 | 2019 |
| Facial expression recognition via joint deep learning of rgb-depth map latent representations OK Oyedotun, G Demisse, A El Rahman Shabayek, D Aouada, ... Proceedings of the IEEE international conference on computer vision …, 2017 | 58 | 2017 |
| Detecting credit card fraud using periodic features AC Bahnsen, D Aouada, A Stojanovic, B Ottersten 2015 IEEE 14th international conference on machine learning and applications …, 2015 | 52 | 2015 |
| Deformation based curved shape representation GG Demisse, D Aouada, B Ottersten IEEE transactions on pattern analysis and machine intelligence 40 (6), 1338-1351, 2017 | 49 | 2017 |
| Depth image enhancement method B Mirbach, T Solignac, FG Becerro, D Aouada US Patent 10,275,857, 2019 | 47 | 2019 |
| Pose encoding for robust skeleton-based action recognition GG Demisse, K Papadopoulos, D Aouada, B Ottersten Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 47 | 2018 |
| Unsupervised vanishing point detection and camera calibration from a single manhattan image with radial distortion M Antunes, JP Barreto, D Aouada, B Ottersten Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 45 | 2017 |
| A survey on deep learning-based monocular spacecraft pose estimation: Current state, limitations and prospects L Pauly, W Rharbaoui, C Shneider, A Rathinam, V Gaudillière, D Aouada Acta Astronautica, 2023 | 42 | 2023 |
| Lspnet: A 2d localization-oriented spacecraft pose estimation neural network A Garcia, MA Musallam, V Gaudilliere, E Ghorbel, K Al Ismaeil, M Perez, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 41 | 2021 |
| Spacecraft recognition leveraging knowledge of space environment: simulator, dataset, competition design and analysis MA Musallam, V Gaudilliere, E Ghorbel, K Al Ismaeil, MD Perez, M Poucet, ... 2021 IEEE International Conference on Image Processing Challenges (ICIPC), 11-15, 2021 | 38 | 2021 |
| 3dbodytex: Textured 3d body dataset A Saint, E Ahmed, K Cherenkova, G Gusev, D Aouada, B Ottersten 2018 International Conference on 3D Vision (3DV), 495-504, 2018 | 33 | 2018 |
| A new multi-lateral filter for real-time depth enhancement F Garcia, D Aouada, B Mirbach, T Solignac, B Ottersten 2011 8th IEEE International Conference on Advanced Video and Signal Based …, 2011 | 32 | 2011 |
| Why is everyone training very deep neural network with skip connections? OK Oyedotun, K Al Ismaeil, D Aouada IEEE Transactions on Neural Networks and Learning Systems 34 (9), 5961-5975, 2022 | 31 | 2022 |
Björn OtterstenProfessor, SnT, University of Luxembourg, KTH Royal Institute of Technology, Stockholm, Sweden確認したメール アドレス: uni.lu
