Martin Längkvist
Martin Längkvist
PhD, Information Technology, AASS Machine Perception and Interaction Lab, Örebro University
Verifierad e-postadress på oru.se - Startsida
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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
7592014
Sleep stage classification using unsupervised feature learning
M Längkvist, L Karlsson, A Loutfi
Advances in Artificial Neural Systems 2012, 2012
2212012
Classification and segmentation of satellite orthoimagery using convolutional neural networks
M Längkvist, A Kiselev, M Alirezaie, A Loutfi
Remote Sensing 8 (4), 329, 2016
2052016
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
312013
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
312011
Learning feature representations with a cost-relevant sparse autoencoder
M Längkvist, A Loutfi
International journal of neural systems 25 (01), 1450034, 2015
192015
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
182018
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
152017
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
102019
Modeling time-series with deep networks
M Längkvist
Örebro university, 2014
92014
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
62016
Learning actions to improve the perceptual anchoring of objects
A Persson, M Längkvist, A Loutfi
Frontiers in Robotics and AI 3, 76, 2017
52017
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
42018
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
42012
A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification
M Längkvist, A Loutfi
arXiv preprint arXiv:1805.05036, 2018
32018
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
22017
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
22016
Learning representations with a dynamic objective sparse autoencoder
M Längkvist, A Loutfi
Neural information processing systems, 2012
22012
Online Identification of Friction Coefficients in an Industrial Robot
M Längkvist
22009
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
12019
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Artiklar 1–20