| 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 | 1489 | 2014 |
| Classification and segmentation of satellite orthoimagery using convolutional neural networks M Längkvist, A Kiselev, M Alirezaie, A Loutfi Remote Sensing 8 (4), 329, 2016 | 370 | 2016 |
| Sleep stage classification using unsupervised feature learning M Längkvist, L Karlsson, A Loutfi Advances in Artificial Neural Systems 2012 (1), 107046, 2012 | 336 | 2012 |
| 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 | 92 | 2018 |
| Inception-v4, inception-ResNet and the impact of residual connections on learning M Längkvist, L Karlsson, A Loutfi Pattern Recognit. Lett 42 (1), 11-24, 2014 | 54 | 2014 |
| 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 | 50 | 2011 |
| 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 | 48 | 2013 |
| 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 | 46 | 2019 |
| 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 | 42 | 2017 |
| Learning feature representations with a cost-relevant sparse autoencoder M Längkvist, A Loutfi International journal of neural systems 25 (01), 1450034, 2015 | 30 | 2015 |
| A symbolic approach for explaining errors in image classification tasks M Alirezaie, M Längkvist, M Sioutis, A Loutfi IJCAI Workshop on Learning and Reasoning. Stockholm, Sweden, 2018 | 24 | 2018 |
| A deep learning approach with an attention mechanism for automatic sleep stage classification M Längkvist, A Loutfi arXiv preprint arXiv:1805.05036, 2018 | 15 | 2018 |
| 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 | 15 | 2016 |
| Modeling time-series with deep networks M Längkvist Örebro university, 2014 | 15 | 2014 |
| An analysis of fast learning methods for classifying forest cover types H Sjöqvist, M Längkvist, F Javed Applied Artificial Intelligence 34 (10), 691-709, 2020 | 13 | 2020 |
| 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 |
| 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 | 5 | 2017 |
| AI unboxed and jobs: A novel measure and firm-level evidence from three countries E Engberg, H Görg, M Lodefalk, F Javed, M Längkvist, NP Monteiro, ... RF Berlin-CReAM Discussion Paper Series, 2024 | 4 | 2024 |
| Deep Learning based Aerial Image Segmentation for Computing Green Area Factor GMA Rahaman, M Längkvist, A Loutfi 2022 10th European Workshop on Visual Information Processing (EUVIP), 1-6, 2022 | 4 | 2022 |
| Performance comparison of two deep learning algorithms in detecting similarities between manual integration test cases C Landin, L Hatvani, S Tahvili, H Haggren, M Längkvist, A Loutfi, ... The Fifteenth International Conference on Software Engineering Advances …, 2020 | 4 | 2020 |
Amy LoutfiProfessor Computer Science, Machine Perception and Interaction Lab, Örebro UniversityVerified email at oru.se
