Michael C Kampffmeyer

Daniel Johansen Trosten; Sigurd Eivindson Løkse; Robert Jenssen; Michael Christian Kampffmeyer; Leveraging tensor kernels to reduce objective function mismatch in deep clustering Pattern Recognition, vol. 149, pp. 0 , (ISSN 0031-3203 1873-5142 ), doi: https://doi.org/10.1016/j.patcog.2023.110229 , 2024. Scientific article

Duy Khoi Tran; van Nhan Nguyen; Davide Roverso; Robert Jenssen; Michael Christian Kampffmeyer; LSNetv2: Improving weakly supervised power line detection with bipartite matching Expert Systems With Applications, pp. 0 , doi: https://doi.org/10.1016/j.eswa.2024.123773 , 2024. Scientific article

Changkyu Choi; Michael Kampffmeyer; Nils Olav Handegard; Arnt-Børre Salberg; Robert Jenssen; Deep Semisupervised Semantic Segmentation in Multifrequency Echosounder Data IEEE Journal of Oceanic Engineering, vol. 48, pp. 384 400 17 , (ISSN 0364-9059 1558-1691 ), doi: https://doi.org/10.1109/JOE.2022.3226214 , 2023. Scientific article

Juan Emmanuel Johnson; Sigurd Eivindson Løkse; Gustau Camps-Valls; Karl Øyvind Mikalsen; Michael Kampffmeyer; et al. The Kernelized Taylor Diagram doi: https://doi.org/10.1007/978-3-031-17030-0_10 , 2023. Scientific chapter / article / conference article

Kristoffer Wickstrøm; Eirik Agnalt Østmo; Keyur Radiya; Karl Øyvind Mikalsen; Michael Kampffmeyer; et al. A clinically motivated self-supervised approach for content-based image retrieval of CT liver images Computerized Medical Imaging and Graphics, vol. 107, pp. 1 12 0 , (ISSN 0895-6111 1879-0771 ), doi: https://doi.org/10.1016/j.compmedimag.2023.102239 , 2023. Scientific article

Daniel Johansen Trosten; Rwiddhi Chakraborty; Sigurd Eivindson Løkse; Kristoffer Wickstrøm; Robert Jenssen; et al. Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings Computer Vision and Pattern Recognition, pp. 7527 7536 , (ISSN 1063-6919 ), doi: https://doi.org/10.1109/CVPR52729.2023.00727 , 2023. Scientific article

Daniel Johansen Trosten; Sigurd Eivindson Løkse; Robert Jenssen; Michael Kampffmeyer; On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering Computer Vision and Pattern Recognition, pp. 23976 23985 , (ISSN 1063-6919 ), doi: https://doi.org/10.1109/CVPR52729.2023.02296 , 2023. Scientific article

Durgesh Kumar Singh; Ahcene Boubekki; Robert Jenssen; Michael Kampffmeyer; Supercm: Revisiting Clustering for Semi-Supervised Learning Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, (ISSN 1520-6149 2379-190X ), doi: https://doi.org/10.1109/ICASSP49357.2023.10095856 , 2023. Scientific article

Eirik Agnalt Østmo; Kristoffer Wickstrøm; Keyur Radiya; Michael Kampffmeyer; Robert Jenssen; View it like a radiologist: Shifted windows for deep learning augmentation of CT images Machine Learning for Signal Processing, pp. 6 , (ISSN 1551-2541 2378-928X ), doi: https://doi.org/10.1109/MLSP55844.2023.10285978 , 2023. Scientific article

Kristoffer Wickstrøm; Sigurd Eivindson Løkse; Michael Kampffmeyer; Shujian Yu; José C. Príncipe; et al. Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy Entropy, vol. 25, pp. 1 21 0 , (ISSN 1099-4300 1099-4300 ), doi: https://doi.org/10.3390/e25060899 , 2023. Scientific article

Ingeborg Mathiesen; Theodor Anton Ross; Anna Kaarina Pöntinen; Einar Holsbø; Michael Kampffmeyer; et al. Characterization of Putative Virulence Factors in Enterococcus faecium 2023. Poster

Kristoffer Knutsen Wickstrøm; Sigurd Eivindson Løkse; Michael Christian Kampffmeyer; Shujian Yu; José C. Príncipe; et al. Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy Entropy, (ISSN 1099-4300 1099-4300 ), doi: https://doi.org/10.3390/e25060899 , 2023. Scientific article

Jonas Lederer; Michael Gastegger; Kristof T. Schütt; Michael Christian Kampffmeyer; Klaus-Robert Müller; et al. Automatic identification of chemical moieties Physical Chemistry, Chemical Physics - PCCP, vol. 25, pp. 26370 26379 9 , (ISSN 1463-9076 1463-9084 ), doi: https://doi.org/10.1039/d3cp03845a , 2023. Scientific article

Luca Tomasetti; Stine Hansen; Mahdieh Khanmohammadi; Kjersti Engan; Liv Jorunn Høllesli; et al. Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation IEEE International Symposium on Biomedical Imaging, pp. 5 , (ISSN 1945-7928 1945-8452 ), doi: https://doi.org/10.1109/ISBI53787.2023.10230655 , 2023. Scientific article

Magnus Oterhals Størdal; Benjamin Ricaud; Michael Christian Kampffmeyer; Geir Bertelsen; Maja Gran Erke; Risk Prediction of Diabetic Retinopathy in the Tromsø Study 2023. Poster

Magnus Oterhals Størdal; Benjamin Ricaud; Michael Christian Kampffmeyer; Geir Bertelsen; Maja Gran Erke; Risk Prediction of Diabetic Retinopathy in the Tromsø Study 2023. Poster

Michael Christian Kampffmeyer; Learning from limited labeled data for few-shot medical image segmentation (and beyond) 2023. Scientific lecture

Michael Christian Kampffmeyer; Hva er kunstig intelligens (KI)? Muligheter og utfordringer 2023. Lecture

Michael Christian Kampffmeyer; AI’S FUTURE PATH, WHAT ARE THE OPPORTUNITIES? 2023. Lecture

Michael Christian Kampffmeyer; UiT Machine Learning Group 2023. Scientific lecture

Michael Christian Kampffmeyer; Self-Explainable Deep Learning 2023. Scientific lecture

Michael Christian Kampffmeyer; Learning from limited labelled data for medical image segmentation 2023. Scientific lecture

Michael Christian Kampffmeyer; Deep Multi-view Clustering 2023. Scientific lecture

Michael Christian Kampffmeyer; Deep Clustering 2023. Scientific lecture

Changkyu Choi; Michael Christian Kampffmeyer; Nils Olav Handegard; Arnt-Børre Salberg; Robert Jenssen; Deep Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data 2023. Poster

Fredrik Emil Aspheim; Samuel Kuttner; Luigi Tommaso Luppino; Rune Sundset; Michael Christian Kampffmeyer; et al. Deep learning derived input-function in dynamic PET-imaging 2023. Lecture

Fredrik Emil Aspheim; Luigi Tommaso Luppino; Michael Christian Kampffmeyer; Robert Jenssen; Rune Sundset; et al. Interpretable deep learning model for input function estimation in small-animal 18F-FDG PET imaging 2023. Scientific lecture

Stine Hansen; Srishti Gautam; Suaiba Amina Salahuddin; Michael Christian Kampffmeyer; Robert Jenssen; ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement Medical Image Analysis, pp. 0 , doi: https://doi.org/10.1016/j.media.2023.102870 , 2023. Scientific article

Kristoffer Wickstrøm; Daniel Johansen Trosten; Sigurd Eivindson Løkse; Ahcene Boubekki; Karl Øyvind Mikalsen; et al. RELAX: Representation Learning Explainability International Journal of Computer Vision, pp. 1584 1610 26 , doi: https://doi.org/10.1007/s11263-023-01773-2 , 2023. Scientific article

Xujie Zhang; Binbin Yang; Michael Christian Kampffmeyer; Wenqing Zhang; Shiyue Zhang; et al. DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment IEEE International Conference on Computer Vision (ICCV), 2023. Scientific article

Haoyuan Li; Haoye Dong; Hanchao Jia; Dong Huang; Michael Christian Kampffmeyer; et al. Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos IEEE International Conference on Computer Vision (ICCV), 2023. Scientific article

Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu; Eric Xing; Federated Partially Supervised Learning With Limited Decentralized Medical Images IEEE Transactions on Medical Imaging, pp. 1944 1954 10 , doi: https://doi.org/10.1109/TMI.2022.3231017 , 2023. Scientific article

Arnt-Børre Salberg; Michael Christian Kampffmeyer; Trends in deep learning 2023. Scientific lecture

Rogelio Andrade Mancisidor; Michael Christian Kampffmeyer; Kjersti Aas; Robert Jenssen; Discriminative multimodal learning via conditional priors in generative models Neural Networks, vol. 169, pp. 417 430 13 , (ISSN 0893-6080 1879-2782 ), doi: https://doi.org/10.1016/j.neunet.2023.10.048 , 2023. Scientific article

Kristoffer Vinther Olesen; Ahcene Boubekki; Michael Christian Kampffmeyer; Robert Jenssen; Anders Nymark Christensen; et al. A Contextually Supported Abnormality Detector for Maritime Trajectories Journal of Marine Science and Engineering, vol. 11, pp. 0 , (ISSN 2077-1312 2077-1312 ), doi: https://doi.org/10.3390/jmse11112085 , 2023. Scientific article

Daniel Johansen Trosten; Sigurd Eivindson Løkse; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen; RELAX: Representation Learning Explainability 2022. Poster

Daniel Johansen Trosten; Kristoffer Wickstrøm; Shujian Yu; Sigurd Eivindson Løkse; Robert Jenssen; et al. Deep Clustering with the Cauchy-Schwarz Divergence 2022. Scientific lecture

Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen; Generating customer's credit behavior with deep generative models Knowledge-Based Systems, vol. 245, pp. 13 , (ISSN 0950-7051 1872-7409 ), doi: https://doi.org/10.1016/j.knosys.2022.108568 , 2022. Scientific article

Kristoffer Wickstrøm; Michael Kampffmeyer; Karl Øyvind Mikalsen; Robert Jenssen; Mixing up contrastive learning: Self-supervised representation learning for time series Pattern Recognition Letters, vol. 155, pp. 54 61 7 , (ISSN 0167-8655 1872-7344 ), doi: https://doi.org/10.1016/j.patrec.2022.02.007 , 2022. Scientific article

Stine Hansen; Srishti Gautam; Michael Kampffmeyer; Robert Jenssen; A self-guided anomaly detection-inspired few-shot segmentation network CEUR Workshop Proceedings, vol. 3271, (ISSN 1613-0073 1613-0073 ), 2022. Scientific article

Stine Hansen; Srishti Gautam; Michael Kampffmeyer; Robert Jenssen; A self-guided anomaly detection-inspired few-shot segmentation network CEUR Workshop Proceedings, vol. 3271, (ISSN 1613-0073 1613-0073 ), 2022. Scientific article

Suaiba Amina Salahuddin; Stine Hansen; Srishti Gautam; Michael Kampffmeyer; Robert Jenssen; A self-guided anomaly detection-inspired few-shot segmentation network CEUR Workshop Proceedings, vol. 3271, (ISSN 1613-0073 1613-0073 ), , 2022. Scientific article

Kristoffer Wickstrøm; Michael Kampffmeyer; Karl Øyvind Mikalsen; Robert Jenssen; Mixing up contrastive learning: Self-supervised representation learning for time series Pattern Recognition Letters, (ISSN 0167-8655 1872-7344 ), doi: https://doi.org/10.1016/j.patrec.2022.02.007 , 2022. Scientific article

Changkyu Choi; Shujian Yu; Michael Kampffmeyer; Arnt-Børre Salberg; Nils Olav Handegard; et al. Explaining Marine Acoustic Target Classification in Multi-channel Echosounder Data using Self-attention Mask, Information-Bottleneck, and Mask Prior 2022. Poster

Kristoffer Wickstrøm; Juan Emmanuel Johnson; Sigurd Eivindson Løkse; Gusatu Camps-Valls; Karl Øyvind Mikalsen; et al. The Kernelized Taylor Diagram Communications in Computer and Information Science, vol. 1650, pp. 125 131 7 , (ISSN 1865-0929 1865-0937 ), doi: https://doi.org/10.1007/978-3-031-17030-0_10 , 2022. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks International Journal of Remote Sensing, vol. 43, pp. 3509 3535 26 , (ISSN 0143-1161 1366-5901 ), doi: https://doi.org/10.1080/01431161.2022.2098078 , 2022. Scientific article

Theodor Anton Ross; Anna Kaarina Pöntinen; Jessin Janice; Einar Holsbø; Jukka Corander; et al. Leveraging machine learning for finding novel putative virulence factors in Enterococcus faecium 2022. Poster

Xujie Zhang; Yu Sha; Michael Kampffmeyer; Zhenyu Xie; Zequn Jie; et al. ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design SIGMM Records, 2022. Scientific article

Srishti Gautam; Marina Marie-Claire Hohne; Stine Hansen; Robert Jenssen; Michael Kampffmeyer; Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation 2022. Poster

Srishti Gautam; Marina Marie-Claire Hohne; Stine Hansen; Robert Jenssen; Michael Kampffmeyer; Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation 2022. Poster

Srishti Gautam; Marina Marie-Claire Hohne; Stine Hansen; Robert Jenssen; Michael Kampffmeyer; Artifact Detection with Prototypical Relevance Propagation 2022. Poster

Zaiyu Huang; Hanhui Li; Zhenyu Xie; Michael Kampffmeyer; Qingling Cai; et al. Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning Advances in Neural Information Processing Systems, pp. 13 , doi: https://doi.org/10.48550/arXiv.2211.14052 , 2022. Scientific article

Xiao Dong; Xunlin Zhan; Yangxin Wu; Yunchao Wei; Michael Kampffmeyer; et al. M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining Computer Vision and Pattern Recognition, pp. 21220 21230 , doi: https://doi.org/10.1109/CVPR52688.2022.02057 , 2022. Scientific article

Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu; Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images Lecture Notes in Computer Science (LNCS), pp. 10 , doi: https://doi.org/10.1007/978-3-031-16452-1_7 , 2022. Scientific article

Srishti Gautam; Ahcene Boubekki; Stine Hansen; Suaiba Amina Salahuddin; Robert Jenssen; et al. ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model Advances in Neural Information Processing Systems, pp. 28 , doi: https://doi.org/10.48550/arXiv.2210.08151 , 2022. Scientific article

Srishti Gautam; Marina Marie-Claire Hohne; Stine Hansen; Robert Jenssen; Michael Kampffmeyer; Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation IEEE International Symposium on Biomedical Imaging, pp. 5 , doi: https://doi.org/10.1109/ISBI52829.2022.9761651 , 2022. Scientific article

Srishti Gautam; Marina Marie-Claire Hohne; Stine Hansen; Robert Jenssen; Michael Kampffmeyer; This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation Pattern Recognition, pp. 13 , doi: https://doi.org/10.1016/j.patcog.2022.109172 , 2022. Scientific article

Kristoffer Wickstrøm; Juan Emmanuel Johnson; Sigurd Eivindson Løkse; Gusatu Camps-Valls; Karl Øyvind Mikalsen; et al. The Kernelized Taylor Diagram 2022. Scientific lecture

Kristoffer Wickstrøm; Eirik Agnalt Østmo; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen; Explaining representations for medical image retrieval 2022. Scientific lecture

Samuel Kuttner; Luigi Tommaso Luppino; Kristoffer Wickstrøm; Nils Thomas Doherty Midtbø; Seyed Esmaeil Dorraji; et al. Deep learning derived input function in dynamic 18F-FDG PET imaging of mice 2022. Scientific lecture

Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu; Eric Xing; Negational symmetry of quantum neural networks for binary pattern classification Pattern Recognition, pp. 9 , doi: https://doi.org/10.1016/j.patcog.2022.108750 , 2022. Scientific article

Luigi Tommaso Luppino; Mads Adrian Hansen; Michael Kampffmeyer; Filippo Maria Bianchi; Gabriele Moser; et al. Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images IEEE Transactions on Neural Networks and Learning Systems, pp. 13 , doi: https://doi.org/10.1109/TNNLS.2022.3172183 , 2022. Scientific article

Stine Hansen; Srishti Gautam; Robert Jenssen; Michael Kampffmeyer; Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels Medical Image Analysis, pp. 12 , doi: https://doi.org/10.1016/j.media.2022.102385 , 2022. Scientific article

Nanqing Dong; Michael Kampffmeyer; Xiaodan Liang; Min Xu; Irina Voiculescu; et al. Towards robust partially supervised multi-structure medical image segmentation on small-scale data Applied Soft Computing, pp. 12 , doi: https://doi.org/10.1016/j.asoc.2021.108074 , 2022. Scientific article

Kristoffer Knutsen Wickstrøm; Daniel Johansen Trosten; Sigurd Eivindson Løkse; Karl Øyvind Mikalsen; Michael Kampffmeyer; et al. RELAX: Representation Learning Explainability 2022. Poster

Kristoffer Knutsen Wickstrøm; Karl Oyvind Mikalsen; Michael Kampffmeyer; Arthur Revhaug; Robert Jenssen; Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series IEEE journal of biomedical and health informatics, vol. 25, pp. 2435 2444 9 , (ISSN 2168-2194 2168-2208 ), doi: https://doi.org/10.1109/JBHI.2020.3042637 , 2021. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; International Journal of Remote Sensing, vol. 42, pp. 6184 6208 , (ISSN 0143-1161 1366-5901 ), doi: https://doi.org/10.1080/01431161.2021.1936267 , 2021. Scientific article

Daniel Johansen Trosten; Robert Jenssen; Michael Kampffmeyer; Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective Proceedings of the Northern Lights Deep Learning Workshop, vol. 2, (ISSN 2703-6928 ), doi: https://doi.org/10.7557/18.5709 , 2021. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; PAGNet Models for The 2nd Agriculture-Vision Challenges CVPR 2021 , 2021. Scientific lecture

Changkyu Choi; Michael Kampffmeyer; Nils Olav Handegard; Arnt Børre Salberg; Olav Brautaset; et al. Semi-supervised target classification in multi-frequency echosounder data ICES Journal of Marine Science, vol. 78, pp. 2615 2627 12 , (ISSN 1054-3139 1095-9289 ), doi: https://doi.org/10.1093/icesjms/fsab140 , 2021. Scientific article

Nils Olav Handegard; Line Eikvil; Robert Jenssen; Michael Kampffmeyer; Arnt Børre Salberg; et al. Machine Learning + Marine Science: Critical Role of Partnerships in Norway Journal of Ocean Technology, vol. 16, pp. 1 9 8 , (ISSN 1718-3200 1718-3219 ), , 2021. Article journal

Changkyu Choi; Michael Kampffmeyer; Nils Olav Handegard; Arnt Børre Salberg; Line Eikvil; et al. Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data 2021. Poster

Michael Kampffmeyer; Robert Jenssen; Karl Øyvind Mikalsen; Sigurd Eivindson Løkse; Towards Explainable Representation Learning 2021. Lecture

Sigurd Eivindson Løkse; Michael Kampffmeyer; Robert Jenssen; Karl Øyvind Mikalsen; Towards Explainable Representation Learning 2021. Lecture

Sigurd Eivindson Løkse; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen; Towards Explainable Representation Learning 2021. Lecture

Stine Hansen; Srishti Gautam; Robert Jenssen; Michael Kampffmeyer; Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision 2021. Scientific lecture

Kristoffer Knutsen Wickstrøm; Karl Øyvind Mikalsen; Michael Kampffmeyer; Arthur Revhaug; Robert Jenssen; Uncertainty-Aware Deep Ensembles for Explainable Time Series Prediction 2021. Scientific lecture

Kristoffer Knutsen Wickstrøm; Michael Kampffmeyer; Robert Jenssen; Advances in explainable DL & how to model uncertainty in explainability 2021. Scientific lecture

Kristoffer Knutsen Wickstrøm; Sigurd Eivindson Løkse; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen; Towards Explainable Representation Learning 2021. Scientific lecture

Michael Kampffmeyer; Deep Clustering 2021. Lecture

Michael Kampffmeyer; Fikk 12 millioner til bildetolking 2021. Media interview

Ahcene Boubekki; Michael Kampffmeyer; Ulf Brefeld; Robert Jenssen; Joint optimization of an autoencoder for clustering and embedding. Machine Learning, pp. 1901 1937 , doi: https://doi.org/10.1007/s10994-021-06015-5 , 2021. Scientific article

Michael Kampffmeyer; UiT-gruppe får millionstøtte for å tolke bilder 2021. Media interview

Zhenyu Xie; Zaiyu Huang; Fuwei Zhao; Haoye Dong; Michael Kampffmeyer; et al. Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN Advances in Neural Information Processing Systems, pp. 12 , doi: https://doi.org/10.48550/arXiv.2111.10544 , 2021. Scientific article

Fuwei Zhao; Zhenyu Xie; Michael Kampffmeyer; Haoye Dong; Songfang Han; et al. M3D-VTON: A Monocular-to-3D Virtual Try-On Network IEEE International Conference on Computer Vision (ICCV), pp. 11 , doi: https://doi.org/10.48550/arXiv.2108.05126 , 2021. Scientific article

Nanqing Dong; Michael Kampffmeyer; Irina Voiculescu; Self-supervised Multi-task Representation Learning for Sequential Medical Images Lecture Notes in Computer Science (LNCS), pp. 779 794 , doi: https://doi.org/10.1007/978-3-030-86523-8_47 , 2021. Scientific article

Daniel Johansen Trosten; Sigurd Eivindson Løkse; Robert Jenssen; Michael Kampffmeyer; Reconsidering Representation Alignment for Multi-View Clustering Computer Vision and Pattern Recognition, pp. 1255 1265 , doi: https://doi.org/10.1109/CVPR46437.2021.00131 , 2021. Scientific article

Luigi Tommaso Luppino; Michael Kampffmeyer; Filippo Maria Bianchi; Gabriele Moser; Sebastiano Bruno Serpico; et al. Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection IEEE Transactions on Geoscience and Remote Sensing, pp. 22 , doi: https://doi.org/10.1109/TGRS.2021.3056196 , 2021. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; Dense dilated convolutions merging network for land cover classification IEEE Transactions on Geoscience and Remote Sensing, vol. 58, pp. 6309 6320 , (ISSN 0196-2892 1558-0644 ), doi: https://doi.org/10.1109/TGRS.2020.2976658 , 2020. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; MSCG-Net Models for The 1st Agriculture-Vision Challenge CVPR 2020 , 2020. Scientific lecture

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; MSCG-Net with Adaptive Class Weighting Loss for Semantic Segmentation , 2020. Scientific lecture

Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen; Deep generative models for reject inference in credit scoring Knowledge-Based Systems, vol. 196, pp. 17 , (ISSN 0950-7051 1872-7409 ), doi: https://doi.org/10.1016/j.knosys.2020.105758 , 2020. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; Multi-View Self-Constructing Graph Convolutional Networks With Adaptive Class Weighting Loss for Semantic Segmentation pp. 199 205 7 , doi: https://doi.org/10.1109/CVPRW50498.2020.00030 , 2020. Scientific chapter / article / conference article

Alba Ordonez; Line Eikvil; Arnt-Børre Salberg; Alf Harbitz; Sean Meling Murray; et al. Explaining decisions of deep neural networks used for fish age prediction PLOS ONE, vol. 15, pp. 19 , (ISSN 1932-6203 1932-6203 ), doi: https://doi.org/10.1371/journal.pone.0235013 , 2020. Scientific article

Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen; Learning latent representations of bank customers with the Variational Autoencoder Expert systems with applications, vol. 164, pp. 13 , (ISSN 0957-4174 1873-6793 ), doi: https://doi.org/10.1016/j.eswa.2020.114020 , 2020. Scientific article

Rogelio Andrade Mancisidor; Michael Kampffmeyer; Kjersti Aas; Robert Jenssen; Learning latent representations of bank customers with the Variational Autoencoder Expert Systems With Applications, vol. 164, pp. 11 , (ISSN 0957-4174 1873-6793 ), doi: https://doi.org/10.1016/j.eswa.2020.114020 , 2020. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; SCG-Net for Semantic Labeling , 2020. Scientific lecture

Changkyu Choi; Filippo Maria Bianchi; Michael Kampffmeyer; Robert Jenssen; Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks Proceedings of the Northern Lights Deep Learning Workshop, (ISSN 2703-6928 ), doi: https://doi.org/10.7557/18.5136 , 2020. Scientific article

Mang Tik Chiu; Xu Xingqiang; Kai Wang; Jennifer Hobbs; Naira Hovakimyan; et al. The 1st Agriculture-Vision Challenge: Methods and Results pp. 212 218 , doi: https://doi.org/10.1109/CVPRW50498.2020.00032 , 2020. Scientific chapter / article / conference article

Michael Kampffmeyer; Robert Jenssen; Karl Øyvind Mikalsen; Arthur Revhaug; Uncertainty-Aware Deep Ensembles for Explainable Time Series Prediction 2020. Lecture

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt-Børre Salberg; Self-Constructing Graph Convolutional Networks for Semantic Labeling pp. 4 , doi: https://doi.org/10.1109/IGARSS39084.2020.9324719 , 2020. Scientific chapter / article / conference article

Stine Hansen; Samuel Kuttner; Michael Kampffmeyer; Tom-Vegard Markussen; Rune Sundset; et al. Unsupervised supervoxel-based lung tumor segmentation across patient scans in hybrid PET/MRI Expert Systems With Applications, pp. 1 12 , doi: https://doi.org/10.1016/j.eswa.2020.114244 , 2020. Scientific article

Changkyu Choi; Michael Kampffmeyer; Robert Jenssen; A Robustness Analysis of Personalized Propagation of Neural Prediction , 2020. Poster

Changkyu Choi; Filippo Maria Bianchi; Michael Kampffmeyer; Robert Jenssen; Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks , 2020. Poster

Qinghui Liu; Michael C. Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images pp. 1 4 4 , doi: https://doi.org/10.1109/JURSE.2019.8809046 , 2019. Scientific chapter / article / conference article

Qinghui Liu; Michael C. Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; DDCM-Net for Semantic Mapping of Remote Sensing Images 2019. Poster

Michael C. Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Lorenzo Livi; Arnt Børre Salberg; et al. Deep divergence-based approach to clustering Neural Networks, vol. 113, pp. 91 101 , (ISSN 0893-6080 1879-2782 ), doi: https://doi.org/10.1016/j.neunet.2019.01.015 , 2019. Scientific article

Filippo Maria Bianchi; Lorenzo Livi; Karl Øyvind Mikalsen; Michael C. Kampffmeyer; Robert Jenssen; Learning representations of multivariate time series with missing data Pattern Recognition, vol. 96:106973, pp. 1 11 , (ISSN 0031-3203 1873-5142 ), doi: https://doi.org/10.1016/j.patcog.2019.106973 , 2019. Scientific article

Qinghui Liu; Michael Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; Road Mapping in Lidar Images Using a Joint-Task Dense Dilated Convolutions Merging Network pp. 5041 5044 , doi: https://doi.org/10.1109/IGARSS.2019.8900082 , 2019. Scientific chapter / article / conference article

Qinghui Liu; Michael C. Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; DDCM Network for Semantic Mapping of Remote Sensing Images , 2019. Scientific lecture

Qinghui Liu; Michael C. Kampffmeyer; Robert Jenssen; Arnt Børre Salberg; Road Mapping in Lidar Images Using a Joint-Task Dense Dilated Convolutions Merging Network , 2019. Scientific lecture

Torgeir Brenn; Lars-Petter Gjøvik; Gunnar Ljosdahl Rasmussen; Tony Bauna; Michael Kampffmeyer; et al. Operationalizing Ship Detection Using Deep Learning , 2019. Scientific lecture

Kristoffer Knutsen Wickstrøm; Michael C. Kampffmeyer; Robert Jenssen; Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps Medical Image Analysis, doi: https://doi.org/10.1016/j.media.2019.101619 , 2019. Scientific article

Yujia Zhang; Michael C. Kampffmeyer; Xiaodan Liang; Dingwen Zhang; Min Tan; et al. Dilated temporal relational adversarial network for generic video summarization Multimedia Tools and Applications, pp. 35237 35261 , doi: https://doi.org/10.1007/s11042-019-08175-y , 2019. Scientific article

Michael C. Kampffmeyer; Yinbo Chen; Xiaodan Liang; Hao Wang; Yujia Zhang; et al. Rethinking knowledge graph propagation for zero-shot learning Computer Vision and Pattern Recognition, pp. 11479 11488 , doi: https://doi.org/10.1109/CVPR.2019.01175 , 2019. Scientific article

Daniel Johansen Trosten; Andreas Storvik Strauman; Michael C. Kampffmeyer; Robert Jenssen; 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, pp. 3257 3261 , doi: https://doi.org/10.1109/ICASSP.2019.8682365 , 2019. Scientific article

Yujia Zhang; Michael C. Kampffmeyer; Xiaoguang Zhao; Min Tan; Deep Reinforcement Learning for Query-Conditioned Video Summarization Applied Sciences, pp. 1 16 , doi: https://doi.org/10.3390/app9040750 , 2019. Scientific article

Michael C. Kampffmeyer; Arnt Børre Salberg; Robert Jenssen; 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, vol. 11, pp. 1758 1768 , (ISSN 1939-1404 2151-1535 ), doi: https://doi.org/10.1109/JSTARS.2018.2834961 , 2018. Scientific article

Michael C. Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Robert Jenssen; Lorenzo Livi; The deep kernelized autoencoder Applied Soft Computing, vol. 71, pp. 816 825 , (ISSN 1568-4946 1872-9681 ), doi: https://doi.org/10.1016/j.asoc.2018.07.029 , 2018. Scientific article

Michael C. Kampffmeyer; Advancing Segmentation and Unsupervised Learning Within the Field of Deep Learning 2018. Doctor dissertat

Yujia Zhang; Michael C. Kampffmeyer; Xiaodan Liang; Min Tan; Eric P. Xing; Query-Conditioned Three-Player Adversarial Network for Video Summarization 2018. Poster

Arnt Børre Salberg; Øivind Due Trier; Michael C. Kampffmeyer; Large-Scale Mapping of Small Roads in Lidar Images Using Deep Convolutional Neural Networks pp. 193 204 , doi: https://doi.org/10.1007%2F978-3-319-59129-2_17 , 2017. Scientific chapter / article / conference article

Michael C. Kampffmeyer; Arnt Børre Salberg; Robert Jenssen; Urban land cover classification with missing data using deep convolutional neural networks pp. 5161 5164 4 , doi: https://doi.org/10.1109/IGARSS.2017.8128164 , 2017. Scientific chapter / article / conference article

Michael C. Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Lorenzo Livi; Arnt Børre Salberg; et al. Deep divergence-based clustering doi: https://doi.org/10.1109/MLSP.2017.8168158 , 2017. Scientific chapter / article / conference article

Michael C. Kampffmeyer; Arnt Børre Salberg; Robert Jenssen; Urban land cover classification with missing data using deep convolutional neural networks , 2017. Scientific lecture

Michael C. Kampffmeyer; Arnt Børre Salberg; Robert Jenssen; Semantic Segmentation of Small Objects and Uncertainty in Urban Remote Sensing Images Using CNNs 2016. Poster

Michael C. Kampffmeyer; Arnt-Børre Salberg; Robert Jenssen; 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, pp. 680 688 , (ISSN 2160-7508 ), doi: https://doi.org/10.1109/CVPRW.2016.90 , 2016. Scientific article

Arnt Børre Salberg; Jarle Bauck Hamar; Florina Ardelean; Thomas Johansen; Michael C. Kampffmeyer; Automatic detection and segmentation of avalanches in remote sensing images using deep convolutional neural networks 2016. Scientific lecture

Michael C. Kampffmeyer; Arnt Børre Salberg; Robert Jenssen; Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks , 2016. Scientific lecture

Øivind Due Trier; Arnt Børre Salberg; Michael C. Kampffmeyer; Automatic mapping of forest roads 2016. Report