| Feature engineering strategies for credit card fraud detection AC Bahnsen, D Aouada, A Stojanovic, B Ottersten Expert Systems with Applications 51, 134-142, 2016 | 360 | 2016 |
| Example-dependent cost-sensitive decision trees AC Bahnsen, D Aouada, B Ottersten Expert Systems with Applications 42 (19), 6609-6619, 2015 | 248 | 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 | 189 | 2013 |
| 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 | 138 | 2014 |
| 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 | 121 | 2018 |
| 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 | 93 | 2014 |
| Deep learning advances on different 3D data representations: A survey E Ahmed, A Saint, AER Shabayek, K Cherenkova, R Das, G Gusev, ... arXiv preprint arXiv:1808.01462 1, 2018 | 67 | 2018 |
| A novel cost-sensitive framework for customer churn predictive modeling AC Bahnsen, D Aouada, B Ottersten Decision Analytics 2 (1), 1-15, 2015 | 64 | 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 | 56 | 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 | 50 | 2017 |
| 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 | 46 | 2018 |
| Deformation based curved shape representation GG Demisse, D Aouada, B Ottersten IEEE transactions on pattern analysis and machine intelligence 40 (6), 1338-1351, 2017 | 46 | 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 | 44 | 2015 |
| 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 | 40 | 2017 |
| Depth image enhancement method B Mirbach, T Solignac, FG Becerro, D Aouada US Patent 10,275,857, 2019 | 38 | 2019 |
| 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 | 33 | 2011 |
| Real‐time depth enhancement by fusion for RGB‐D cameras F Garcia, D Aouada, T Solignac, B Mirbach, B Ottersten IET Computer Vision 7 (5), 335-345, 2013 | 31 | 2013 |
| Squigraphs for fine and compact modeling of 3-D shapes D Aouada, H Krim IEEE transactions on image processing 19 (2), 306-321, 2009 | 28 | 2009 |
| Rgb-d multi-view system calibration for full 3d scene reconstruction H Afzal, D Aouada, D Font, B Mirbach, B Ottersten 2014 22nd International Conference on Pattern Recognition, 2459-2464, 2014 | 27 | 2014 |
| Visual and human-interpretable feedback for assisting physical activity M Antunes, R Baptista, G Demisse, D Aouada, B Ottersten Computer Vision–ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8 …, 2016 | 26 | 2016 |
Björn OtterstenProfessor, SnT,University of Luxembourg, KTH Royal Institute of Technology, Stockholm, SwedenVerified email at uni.lu
