| A review of unsupervised feature learning and deep learning for time-series modeling M Längkvist, L Karlsson, A Loutfi Pattern Recognition Letters 42, 11-24, 2014 | 811 | 2014 |
| Sleep stage classification using unsupervised feature learning M Längkvist, L Karlsson, A Loutfi Advances in Artificial Neural Systems 2012, 2012 | 236 | 2012 |
| Classification and segmentation of satellite orthoimagery using convolutional neural networks M Längkvist, A Kiselev, M Alirezaie, A Loutfi Remote Sensing 8 (4), 329, 2016 | 215 | 2016 |
| Fast classification of meat spoilage markers using nanostructured ZnO thin films and unsupervised feature learning M Längkvist, S Coradeschi, A Loutfi, JBB Rayappan Sensors 13 (2), 1578-1592, 2013 | 33 | 2013 |
| Unsupervised feature learning for electronic nose data applied to bacteria identification in blood M Längkvist, A Loutfi NIPS 2011 workshop on deep learning and unsupervised feature learning, 2011 | 32 | 2011 |
| Computer aided detection of ureteral stones in thin slice computed tomography volumes using convolutional neural networks M Längkvist, J Jendeberg, P Thunberg, A Loutfi, M Lidén Computers in biology and medicine 97, 153-160, 2018 | 21 | 2018 |
| Learning feature representations with a cost-relevant sparse autoencoder M Längkvist, A Loutfi International journal of neural systems 25 (01), 1450034, 2015 | 20 | 2015 |
| An ontology-based reasoning framework for querying satellite images for disaster monitoring M Alirezaie, A Kiselev, M Längkvist, F Klügl, A Loutfi Sensors 17 (11), 2545, 2017 | 19 | 2017 |
| Semantic referee: A neural-symbolic framework for enhancing geospatial semantic segmentation M Alirezaie, M Längkvist, M Sioutis, A Loutfi Semantic Web 10 (5), 863-880, 2019 | 12 | 2019 |
| Modeling time-series with deep networks M Längkvist Örebro university, 2014 | 9 | 2014 |
| Interactive learning with convolutional neural networks for image labeling M Längkvist, M Alirezaie, A Kiselev, A Loutfi International Joint Conference on Artificial Intelligence (IJCAI), New York …, 2016 | 6 | 2016 |
| Learning actions to improve the perceptual anchoring of objects A Persson, M Längkvist, A Loutfi Frontiers in Robotics and AI 3, 76, 2017 | 5 | 2017 |
| A symbolic approach for explaining errors in image classification tasks M Alirezaie, M Längkvist, M Sioutis, A Loutfi Working Papers and Documents of the IJCAI-ECAI-2018 Workshop on, 2018 | 4 | 2018 |
| A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification M Längkvist, A Loutfi arXiv preprint arXiv:1805.05036, 2018 | 4 | 2018 |
| Not all signals are created equal: Dynamic objective auto-encoder for multivariate data M Längkvist, A Loutfi NIPS Workshop on Deep Learning and Unsupervised Feature Learning, 2012, 2012 | 4 | 2012 |
| Exploiting Context and Semantics for UAV Path-Finding in an Urban Setting M Alirezaie, A Kiselev, F Klügl, M Längkvist, A Loutfi International Workshop on Application of Semantic Web technologies in …, 2017 | 2 | 2017 |
| Open GeoSpatial Data as a Source of Ground Truth for Automated Labelling of Satellite Images M Alirezaie, M Längkvist, A Kiselev, A Loutfi The 9th International Conference on Geographic Information Science …, 2016 | 2 | 2016 |
| Learning representations with a dynamic objective sparse autoencoder M Längkvist, A Loutfi Neural information processing systems, 2012 | 2 | 2012 |
| Online Identification of Friction Coefficients in an Industrial Robot M Längkvist | 2 | 2009 |
| Interactive user interface based on Convolutional Auto-encoders for annotating CT-scans M Längkvist, J Widell, P Thunberg, A Loutfi, M Lidén arXiv preprint arXiv:1904.11701, 2019 | 1 | 2019 |
Amy LoutfiProfessor Information Technology, AASS Machine Perception and Interaction Lab, Örebro UniversityVerified email at oru.se
