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2020
1 Kuttner, Samuel; Knutsen Wickstrøm, Kristoffer; Kalda, Gustav; Dorraji, Seyed Esmaeil; Martin, armas maria montserrat; Oteiza, Ana; Jenssen, Robert; Fenton, Kristin Andreassen; Sundset, Rune; Axelsson, Jan.
Machine learning derived input-function in a dynamic 18F-FDG PET study of mice. Biomedical engineering and physics express 2020
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2 Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre.
Dense Dilated Convolutions Merging Network for Land Cover Classification. IEEE Transactions on Geoscience and Remote Sensing 2020
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2019
3 Bianchi, Filippo Maria; Livi, Lorenzo; Mikalsen, Karl Øyvind; Kampffmeyer, Michael C.; Jenssen, Robert.
Learning representations of multivariate time series with missing data. Pattern Recognition 2019 ;Volum 96:106973. s. 1-11
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4 Kampffmeyer, Michael C.; Løkse, Sigurd; Bianchi, Filippo Maria; Livi, Lorenzo; Salberg, Arnt Børre; Jenssen, Robert.
Deep divergence-based approach to clustering. Neural Networks 2019 ;Volum 113. s. 91-101
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5 Kocbek, Primoz; Fijacko, Nino; Ruiz, Cristina Soguero; Mikalsen, Karl Øyvind; Maver, Uros; Brzan, Petra Povalej; Stozer, Andraz; Jenssen, Robert; Skrøvseth, Stein Olav; Stiglic, Gregor.
Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative Temporal Data. Computational & Mathematical Methods in Medicine 2019 ;Volum 2019.
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6 Liu, Qinghui; Kampffmeyer, Michael C.; Jenssen, Robert; Salberg, Arnt Børre.
DDCM Network for Semantic Mapping of Remote Sensing Images. NLDL2019: Northern Lights Deep Learning Workshop; 2019-01-08 - 2019-01-10
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7 Liu, Qinghui; Kampffmeyer, Michael C.; Jenssen, Robert; Salberg, Arnt Børre.
Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images. I: Joint Urban Remote Sensing Event, JURSE 2019. IEEE 2019 ISBN 978-1-7281-0009-8. s. 1-4
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8 Liu, Qinghui; Kampffmeyer, Michael C.; Jenssen, Robert; Salberg, Arnt Børre.
Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images. JURSE2019 -Joint Urban Remote Sensing Event; 2019-05-22 - 2019-05-24
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9 Liu, Qinghui; Kampffmeyer, Michael C.; Jenssen, Robert; Salberg, Arnt Børre.
Road Mapping in Lidar Images Using a Joint-Task Dense Dilated Convolutions Merging Network. IGARSS 2019; 2019-07-27 - 2019-08-02
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10 Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre.
Road Mapping in Lidar Images Using a Joint-Task Dense Dilated Convolutions Merging Network. I: IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium Proceedings. IEEE 2019 ISBN 978-1-5386-9154-0. s. 5041-5044
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11 Mikalsen, Karl Øyvind.
Advancing Unsupervised and Weakly Supervised Learning with Emphasis on Data-Driven Healthcare. : UiT Norges arktiske universitet 2019 201 s.
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12 Mikalsen, Karl Øyvind; Soguero-Ruiz, Cristina; Bianchi, Filippo Maria; Jenssen, Robert.
Noisy multi-label semi-supervised dimensionality reduction. Pattern Recognition 2019 ;Volum 90. s. 257-270
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13 Nguyen, van Nhan; Jenssen, Robert; Roverso, Davide.
Intelligent Monitoring and Inspection of Power Line Components Powered by UAVs and Deep Learning. IEEE Power and Energy Technology Systems Journal 2019 ;Volum 6.(1) s. 11-21
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14 Trosten, Daniel Johansen; Strauman, Andreas Storvik; Kampffmeyer, Michael C.; Jenssen, Robert.
Recurrent Deep Divergence-based Clustering for Simultaneous Feature Learning and Clustering of Variable Length Time Series. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2019 ;Volum 2019-May. s. 3257-3261
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15 Wickstrøm, Kristoffer Knutsen; Kampffmeyer, Michael C.; Jenssen, Robert.
Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps. Medical Image Analysis 2019
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2018
16 Bianchi, Filippo Maria; Mikalsen, Karl Øyvind; Jenssen, Robert.
Learning compressed representations of blood samples time series with missing data. I: ESANN 2018 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. : i6doc.com 2018 s. -
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17 Bianchi, Filippo Maria; Scardapane, Simone; Løkse, Sigurd; Jenssen, Robert.
Bidirectional deep-readout echo state networks. I: ESANN 2018 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. : i6doc.com 2018 s. 425-430
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18 Hansen, Mads Adrian; Mikalsen, Karl Øyvind; Kampffmeyer, Michael C.; Soguero-Ruiz, Cristina; Jenssen, Robert.
Towards deep anchor learning. I: 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI 2018). IEEE 2018 ISBN 9781538624067. s. 315-318
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19 Kampffmeyer, Michael C..
Advancing Segmentation and Unsupervised Learning Within the Field of Deep Learning. : UiT Norges arktiske universitet 2018 196 s.
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20 Kampffmeyer, Michael C.; Løkse, Sigurd; Bianchi, Filippo Maria; Jenssen, Robert; Livi, Lorenzo.
The deep kernelized autoencoder. Applied Soft Computing 2018 ;Volum 71. s. 816-825
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21 Kampffmeyer, Michael C.; Salberg, Arnt Børre; Jenssen, Robert.
Urban land cover classification with missing data modalities using deep convolutional neural networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2018 ;Volum 11.(6) s. 1758-1768
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22 Liu, Qinghui; Salberg, Arnt Børre; Jenssen, Robert.
A COMPARISON OF DEEP LEARNING ARCHITECTURES FOR SEMANTIC MAPPING OF VERY HIGH RESOLUTION IMAGES. 2018 International Geoscience and Remote Sensing Symposium; 2018-07-22 - 2018-07-27
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23 Liu, Qinghui; Salberg, Arnt Børre; Jenssen, Robert.
A Comparison of Deep Learning Architectures for Semantic Mapping of Very High Resolution Images. I: IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE conference proceedings 2018 ISBN 978-1-5386-7150-4. s. 6943-6946
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24 Løkse, Sigurd; Jenssen, Robert.
Ranking Using Transition Probabilities Learned from Multi-Attribute Data. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2018 ;Volum 2018-April. s. 2851-2855
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25 Mikalsen, Karl Øyvind; Soguero-Ruiz, Cristina; Mora-Jiménez, Inmaculada; Caballero López Fando, Isabel; Jenssen, Robert.
Using multi-anchors to identify patients suffering from multimorbidities. I: 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE 2018 ISBN 978-1-5386-5488-0. s. 1514-1521
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26 Nguyen, van Nhan; Jenssen, Robert; Roverso, Davide.
Automatic autonomous vision-based power line inspection: A review of current status and the potential role of deep learning. International Journal of Electrical Power & Energy Systems 2018 ;Volum 99. s. 107-120
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27 Strauman, Andreas Storvik; Bianchi, Filippo Maria; Mikalsen, Karl Øyvind; Kampffmeyer, Michael C.; Soguero-Ruiz, Cristina; Jenssen, Robert.
Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks. I: 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI 2018). IEEE 2018 ISBN 9781538624067. s. 307-310
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28 Wickstrøm, Kristoffer Knutsen; Kampffmeyer, Michael C.; Jenssen, Robert.
Uncertainty modeling and interpretability in convolutional neural networks for polyp segmentation. I: 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE Signal Processing Society 2018 ISBN 978-1-5386-5477-4.
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2017
29 Bianchi, Filippo Maria; Kampffmeyer, Michael C.; Maiorino, Enrico; Jenssen, Robert.
Temporal overdrive recurrent neural network. I: 2017 International Joint Conference on Neural Networks (IJCNN). IEEE 2017 ISBN 978-1-5090-6182-2. s. 4275-4282
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30 Bianchi, Filippo Maria; Livi, Lorenzo; Alippi, Cesare; Jenssen, Robert.
Multiplex visibility graphs to investigate recurrent neural network dynamics. Scientific Reports 2017 ;Volum 7. s. 1-13
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31 Bianchi, Filippo Maria; Livi, Lorenzo; Jenssen, Robert; Alippi, Cesare.
Critical echo state network dynamics by means of Fisher information maximization. I: 2017 International Joint Conference on Neural Networks (IJCNN). IEEE 2017 ISBN 978-1-5090-6182-2. s. 852-858
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32 Bianchi, Filippo Maria; Maiorino, Enrico; Kampffmeyer, Michael C.; Rizzi, Antonello; Jenssen, Robert.
Recurrent Neural Networks for Short-Term Load Forecasting: An Overview and Comparative Analysis. Springer 2017 (ISBN 978-3-319-70338-1) 74 s. SpringerBriefs in Computer Science(1)
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33 Kampffmeyer, Michael C.; Løkse, Sigurd; Bianchi, Filippo Maria; Jenssen, Robert; Livi, Lorenzo.
Deep kernelized autoencoders. Lecture Notes in Computer Science (LNCS) 2017 ;Volum 10269 LNCS. s. 419-430
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34 Kampffmeyer, Michael C.; Løkse, Sigurd; Bianchi, Filippo Maria; Livi, Lorenzo; Salberg, Arnt Børre; Jenssen, Robert.
Deep divergence-based clustering. I: 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE Signal Processing Society 2017 ISBN 978-1-5090-6341-3.
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35 Kampffmeyer, Michael C.; Salberg, Arnt Børre; Jenssen, Robert.
Urban land cover classification with missing data using deep convolutional neural networks. 2017 IEEE International Geoscience and Remote Sensing Symposium; 2017-07-23 - 2017-07-28
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36 Kampffmeyer, Michael C.; Salberg, Arnt Børre; Jenssen, Robert.
Urban land cover classification with missing data using deep convolutional neural networks. I: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE 2017 ISBN 978-1-5090-4951-6. s. 5161-5164
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37 Luppino, Luigi Tommaso; Anfinsen, Stian Normann; Moser, Gabriele; Jenssen, Robert; Bianchi, Filippo Maria; Serpico, Sebastian Bruno; Mercier, Gregoire.
A clustering approach to heterogeneous change detection. I: Image Analysis 20th Scandinavian Conference, SCIA 2017 Tromsø, Norway, June 12–14, 2017 Proceedings, Part II. Springer 2017 ISBN 978-3-319-59128-5. s. 181-192
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38 Løkse, Sigurd; Bianchi, Filippo Maria; Jenssen, Robert.
Training Echo State Networks with Regularization Through Dimensionality Reduction. Cognitive Computation 2017 ;Volum 9.(3) s. 364-378
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39 Løkse, Sigurd; Bianchi, Filippo Maria; Salberg, Arnt Børre; Jenssen, Robert.
Spectral clustering using PCKID ? A probabilistic cluster kernel for incomplete data. Lecture Notes in Computer Science (LNCS) 2017 ;Volum 10269 LNCS. s. 431-442
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40 Mikalsen, Karl Øyvind; Bianchi, Filippo Maria; Ruiz, Cristina Soguero; Jenssen, Robert.
The time series cluster kernel. I: 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE Signal Processing Society 2017 ISBN 978-1-5090-6341-3. s. -
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41 Mikalsen, Karl Øyvind; Bianchi, Filippo Maria; Ruiz, Cristina Soguero; Jenssen, Robert.
Time series cluster kernel for learning similarities between multivariate time series with missing data. Pattern Recognition 2017 ;Volum 76. s. 569-581
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42 Mikalsen, Karl Øyvind; Ruiz, Cristina Soguero; Jensen, Kasper; Hindberg, Kristian; Gran, Mads; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Skrøvseth, Stein Olav; Godtliebsen, Fred; Jenssen, Robert.
Using anchors from free text in electronic health records to diagnose postoperative delirium. Computer Methods and Programs in Biomedicine 2017 ;Volum 152. s. 105-114
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43 Myhre, Jonas Nordhaug; Jenssen, Robert; Mikalsen, Karl Øyvind; Løkse, Sigurd.
Robust clustering using a kNN mode seeking ensemble. Pattern Recognition 2017 ;Volum 76. s. 491-505
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44 Myhre, Jonas Nordhaug; Kampffmeyer, Michael C.; Jenssen, Robert.
Density ridge manifold traversal. I: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE conference proceedings 2017 ISBN 978-1-5090-4117-6. s. 2342-2346
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45 Os, Vibeke; Jenssen, Robert.
Lager system i et kaos av digital informasjon. uit.no/nyheter [Internett] 2017-01-16
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2016
46 Blix, Katalin; Camps-Valls, Gustau; Jenssen, Robert.
Gaussian Process Sensitivity Analysis for Oceanic Chlorophyll Estimation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2016 ;Volum 10.(4) s. 1265-1277
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47 Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gómez-Chova, Luis; Camps-Valls, Gustau.
Optimized Kernel Entropy Components. IEEE Transactions on Neural Networks and Learning Systems 2016 ;Volum 28.(6) s. 1466-1472
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48 Kampffmeyer, Michael C.; Salberg, Arnt Børre; Jenssen, Robert.
Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks. IEEE Conference on Computer Vision and Pattern Recognition Workshops; 2016-07-01
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49 Kampffmeyer, Michael C.; Salberg, Arnt Børre; Jenssen, Robert.
Semantic Segmentation of Small Objects and Uncertainty in Urban Remote Sensing Images Using CNNs. CIFAR-CRM Deep Learning Summer School 2016; 2016-08-07
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50 Kampffmeyer, Michael C.; Salberg, Arnt-Børre; Jenssen, Robert.
Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks. IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops 2016 s. 680-688
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