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For å registrere i Cristin må du være vitenskapelig eller administrativt ansatt.
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2021
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| 1. | Luppino, Luigi Tommaso; Kampffmeyer, Michael; Bianchi, Filippo Maria; Moser, Gabriele; Serpico, Sebastian Bruno; Jenssen, Robert; Anfinsen, Stian Normann. Deep image translation with an affinity-based change prior for unsupervised multimodal change detection. IEEE Transactions on Geoscience and Remote Sensing 2021 UiT |
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| 2. | Mikalsen, Karl Øyvind; Ruiz, Cristina Soguero; Bianchi, Filippo Maria; Revhaug, Arthur; Jenssen, Robert. Time series cluster kernels to exploit informative missingness and incomplete label information. Pattern Recognition 2021 UiT |
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2020
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| 3. | Andrade Mancisidor, Rogelio; Kampffmeyer, Michael; Aas, Kjersti; Jenssen, Robert. Deep generative models for reject inference in credit scoring. Knowledge-Based Systems 2020 ;Volum 196. s. - NR UiT |
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| 4. | Andrade Mancisidor, Rogelio; Kampffmeyer, Michael; Aas, Kjersti; Jenssen, Robert. Learning latent representations of bank customers with the Variational Autoencoder. Expert systems with applications 2020 ;Volum 164. s. - NR UiT |
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| 5. | Andrade Mancisidor, Rogelio; Kampffmeyer, Michael; Aas, Kjersti; Jenssen, Robert. Learning latent representations of bank customers with the Variational Autoencoder. Expert systems with applications 2020 ;Volum 164. s. - NR UiT |
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| 6. | Bianchi, Filippo Maria; Scardapane, Simone; Løkse, Sigurd; Jenssen, Robert. Reservoir computing approaches for representation and classification of multivariate time series. IEEE Transactions on Neural Networks and Learning Systems 2020 s. - NORCE UiT |
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| 7. | Chiu, Mang Tik; Xingqiang, Xu; Wang, Kai; Hobbs, Jennifer; Hovakimyan, Naira; Huang, Thomas S.; Shi, Honghui; Wei, Yunchao; Huang, Zilong; Schwing, Alexander; Brunner, Robert; Dozier, Ivan; Dozier, Wyatt; Ghandilyan, Karen; Wilson, David; Park, Hyunseong; Kim, Junhee; Kim, Sungho; Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre; Barbosa, Alexandre; Trevisan, Rodrigo; Zhao, Bingchen; Yu, Shaozuo; Yang, Siwei; Wang, Yin; Sheng, Hao; Chen, Xiao; Su, Jingyi; Rajagopal, Ram; Ng, Andrew; Huynh, Van Thong; Kim, Soo-Hyung; Na, In-Seop; Baid, Ujjwal; Innani, Shubham; Dutande, Prasad; Baheti, Bhakti; Talbar, Sanjay; Tang, Jianyu. The 1st Agriculture-Vision Challenge: Methods and Results. I: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2020. IEEE 2020 ISBN 978-1-7281-9360-1. s. 212-218 NR UiT |
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| 8. | Choi, Changkyu; Bianchi, Filippo Maria; Kampffmeyer, Michael; Jenssen, Robert. Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks. Northern Lights Deep Learning Workshop (NLDL) 2020; 2020-01-19 - 2020-01-21 NORCE UiT |
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| 9. | Choi, Changkyu; Bianchi, Filippo Maria; Kampffmeyer, Michael; Jenssen, Robert. Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks. Proceedings of the Northern Lights Deep Learning Workshop 2020 ;Volum 1. s. - NORCE UiT |
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| 10. | Choi, Changkyu; Kampffmeyer, Michael; Jenssen, Robert. A Robustness Analysis of Personalized Propagation of Neural Prediction. Northern Lights Deep Learning Workshop (NLDL) 2020; 2020-01-19 - 2020-01-21 UiT |
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| 11. | Hansen, Stine; Kuttner, Samuel; Kampffmeyer, Michael; Markussen, Tom-Vegard; Sundset, Rune; Øen, Silje Kjærnes; Eikenes, Live; Jenssen, Robert. Unsupervised supervoxel-based lung tumor segmentation across patient scans in hybrid PET/MRI. Expert systems with applications 2020 NTNU UiT UNN |
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| 12. | Wickstrøm, Kristoffer Knutsen; Mikalsen, Karl Øyvind; Kampffmeyer, Michael; Revhaug, Arthur; Jenssen, Robert. Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series. IEEE journal of biomedical and health informatics 2020 NR UiT UNN |
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| 13. | Yu, Shujian; Wickstrøm, Kristoffer Knutsen; Jenssen, Robert; Principe, Jose. Understanding Convolutional Neural Networks With Information Theory: An Initial Exploration. IEEE Transactions on Neural Networks and Learning Systems 2020 ;Volum 32.(1) s. 436-442 UiT |
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| 14. | Kuttner, Samuel; Wickstrøm, Kristoffer Knutsen; Kalda, Gustav; Dorraji, Seyed Esmaeil; Martin-Armas, 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 & Physics Express 2020 ;Volum 6:015020. s. 1-13 OUS UiT UNN |
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| 15. | 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 ;Volum 58.(9) s. 6309-6320 NR UiT |
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| 16. | Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. MSCG-Net Models for The 1st Agriculture-Vision Challenge. CVPR 2020 Workshop on AGRICULTURE-VISION; 2020-06-14 - 2020-06-19 NR UiT |
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| 17. | Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. MSCG-Net with Adaptive Class Weighting Loss for Semantic Segmentation. CVPR 2020 Workshop on AGRICULTURE-VISION; 2020-06-14 - 2020-06-19 NR UiT |
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| 18. | Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. Multi-View Self-Constructing Graph Convolutional Networks With Adaptive Class Weighting Loss for Semantic Segmentation. I: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2020. IEEE 2020 ISBN 978-1-7281-9360-1. s. 199-205 NR UiT |
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| 19. | Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. SCG-Net for Semantic Labeling. IGARSS 2020; 2020-09-26 - 2020-10-02 NR UiT |
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| 20. | Mikalsen, Karl Øyvind; Soguero-Ruiz, Cristina; Jenssen, Robert. A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs. I: Explainable AI in Healthcare and Medicine. Springer 2020 ISBN 9783030533519. UiT UNN |
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2019
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| 21. | 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 NR UiT |
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| 22. | Brenn, Torgeir; Gjøvik, Lars-Petter; Rasmussen, Gunnar Ljosdahl; Bauna, Tony; Kampffmeyer, Michael; Jenssen, Robert; Anfinsen, Stian Normann. Operationalizing Ship Detection Using Deep Learning. Maritime Situational Awareness Workshop (MSAW 2019); 2019-10-08 - 2019-10-10 UiT |
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| 23. | 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 NR UiT |
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| 24. | 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. UiT UNN |
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| 25. | 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 NR UiT |
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| 26. | Liu, Qinghui; Kampffmeyer, Michael C.; Jenssen, Robert; Salberg, Arnt Børre. DDCM-Net for Semantic Mapping of Remote Sensing Images. JURSE2019 -Joint Urban Remote Sensing Event; 2019-05-22 - 2019-05-24 NR UiT |
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| 27. | 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 NR UiT |
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| 28. | 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 NR UiT |
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| 29. | 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 NR UiT |
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| 30. | Mikalsen, Karl Øyvind. Advancing Unsupervised and Weakly Supervised Learning with Emphasis on Data-Driven Healthcare. : UiT Norges arktiske universitet 2019 201 s. UiT |
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| 31. | 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 UiT |
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| 32. | 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 UiT |
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| 33. | 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 UiT |
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| 34. | 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 UiT |
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2018
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| 35. | 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. - UiT |
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| 36. | 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 UiT |
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| 37. | 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 UiT |
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| 38. | Kampffmeyer, Michael C.. Advancing Segmentation and Unsupervised Learning Within the Field of Deep Learning. : UiT Norges arktiske universitet 2018 196 s. UiT |
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| 39. | 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 NR UiT |
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| 40. | 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 NR UiT |
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| 41. | 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 NR UiT |
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| 42. | 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 NR UiT |
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| 43. | 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 UiT |
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| 44. | 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 UiT |
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| 45. | 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 UiT |
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| 46. | 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 UiT |
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| 47. | 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. UiT |
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2017
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| 48. | 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 UiT |
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| 49. | 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 UiT |
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| 50. | 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 UiT |
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