Cristin

2021
1.	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 2021 ;Volum 32.(5) s. 2169-2179 UiT NORCE Untitled

2.	Boubekki, Ahcene; Kampffmeyer, Michael; Brefeld, Ulf; Jenssen, Robert. Joint optimization of an autoencoder for clustering and embedding. Machine Learning 2021 ;Volum 110. UiT Untitled

3.	Choi, Changkyu; Kampffmeyer, Michael; Handegard, Nils Olav; Salberg, Arnt Børre; Brautaset, Olav; Eikvil, Line; Jenssen, Robert. Semi-supervised target classification in multi-frequency echosounder data. ICES Journal of Marine Science 2021 s. - HAVFORSK UiT NR Untitled

4.	Escudero-Arnanz, Oscar; Rodríguez-Álvarez, Joaquín; Mikalsen, Karl Øyvind; Jenssen, Robert; Soguero-Ruiz, Cristina. On the Use of Time Series Kernel and Dimensionality Reduction to Identify the Acquisition of Antimicrobial Multidrug Resistance in the Intensive Care Unit. 2021 KDD Workshop on Applied Data Science for Healthcare; 2021-08-15 - 2021-08-16 UiT Untitled

5.	Handegard, Nils Olav; Eikvil, Line; Jenssen, Robert; Kampffmeyer, Michael; Salberg, Arnt Børre; Malde, Ketil. Machine Learning + Marine Science: Critical Role of Partnerships in Norway. Journal of Ocean Technology 2021 ;Volum 16.(3) s. - HAVFORSK NR Untitled

6.	Trosten, Daniel Johansen; Jenssen, Robert; Kampffmeyer, Michael. Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective. Proceedings of the Northern Lights Deep Learning Workshop 2021 ;Volum 2. UiT NR Untitled

7.	Kuttner, Samuel; Wickstrøm, Kristoffer Knutsen; Lubberink, Mark; Tolf, Andreas; Burman, Joachim; Sundset, Rune; Jenssen, Robert; Appel, Lieuwe; Axelsson, Jan. Cerebral blood flow measurements with <sup>15</sup>O-water PET using a non-invasive machine-learning-derived arterial input function. Journal of Cerebral Blood Flow and Metabolism 2021 s. 1-13 UiT UNN Untitled

8.	Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. PAGNet Models for The 2nd Agriculture-Vision Challenges CVPR 2021. CVPR 2021 Workshop on AGRICULTURE-VISION; 2021-06-20 - 2021-06-21 NR UiT Untitled

9.	Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. Self-constructing graph neural networks to model long-range pixel dependencies for semantic segmentation of remote sensing images. International Journal of Remote Sensing 2021 NR UiT Untitled

10.	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 Untitled

11.	Luppino, Luigi Tommaso; Kampffmeyer, Michael; Bianchi, Filippo Maria; Moser, Gabriele; Serpico, Sebastiano 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 NORCE UiT Untitled

12.	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 Untitled

13.	Nguyen, Van Nhan; Jenssen, Robert; Roverso, Davide. LS-Net: fast single-shot line-segment detector. Machine Vision and Applications 2021 ;Volum 32.(1) s. - UiT Untitled

14.	Trosten, Daniel Johansen; Løkse, Sigurd Eivindson; Jenssen, Robert; Kampffmeyer, Michael. Reconsidering Representation Alignment for Multi-View Clustering. Computer Vision and Pattern Recognition 2021 UiT Untitled

15.	Wickstrøm, Kristoffer Knutsen; Mikalsen, Karl Oyvind; 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 2021 ;Volum 25.(7) s. 2435-2444 UiT UNN NR Untitled
2020
16.	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 Untitled

17.	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 Untitled

18.	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 Untitled

19.	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 Untitled

20.	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 Untitled

21.	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 Untitled

22.	Goodwin, Morten; Pettersen, Klas Henning; Jenssen, Robert. Episode 1 - Robert Jenssen forklarer kunstig intelligens innen helseforskning, computer vision og bildanalyse. NORA forklarer kunstig intelligens [Internett] 2020-12-15 UIA UiT Untitled

23.	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 ;Volum 167:114244. s. 1-12 UNN UiT NTNU Untitled

24.	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 Untitled

25.	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 UiT UNN OUS Untitled

26.	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 Untitled

27.	Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. MSCG-Net Models for The 1st Agriculture-Vision Challenge CVPR 2020. CVPR 2020 Workshop on AGRICULTURE-VISION; 2020-06-14 - 2020-06-19 NR UiT Untitled

28.	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 Untitled

29.	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 Untitled

30.	Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt Børre. SCG-Net for Semantic Labeling. IGARSS 2020; 2020-09-26 - 2020-10-02 NR UiT Untitled

31.	Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt-Børre. Self-Constructing Graph Convolutional Networks for Semantic Labeling. I: IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. Proceedings. IEEE 2020 ISBN 9781728163741. s. - NR UiT Untitled

32.	Mikalsen, Karl Øyvind; Ruiz, Cristina Soguero; 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 Untitled

33.	Yu, Shujian; Giraldo, Luis Gonzalo Sánchez; Jenssen, Robert; Principe, Jose C.. Multivariate Extension of Matrix-Based Rényi's αα-Order Entropy Functional. IEEE Transactions on Pattern Analysis and Machine Intelligence 2020 ;Volum 42.(11) s. 2960-2966 UiT Untitled
2019
34.	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 Untitled

35.	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 Untitled

36.	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 Untitled

37.	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 Untitled

38.	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 Untitled

39.	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 Untitled

40.	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 Untitled

41.	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 Untitled

42.	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 Untitled

43.	Mikalsen, Karl Øyvind. Advancing Unsupervised and Weakly Supervised Learning with Emphasis on Data-Driven Healthcare. : UiT Norges arktiske universitet 2019 201 s. UiT Untitled

44.	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 Untitled

45.	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 Untitled

46.	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 Untitled

47.	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 Untitled
2018
48.	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 Untitled

49.	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 Untitled

50.	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 Untitled

Vis neste liste