Seniorforsker II

Michael C Kampffmeyer

Publikasjoner

  • 80 publikasjoner funnet
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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. Vitenskapelig artikkel

Utgiver MDPI

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. Vitenskapelig artikkel

Utgiver IEEE Oceanic Engineering Society

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. Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

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. Vitenskapelig artikkel

Utgiver Pergamon Press

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. Vitenskapelig artikkel

Utgiver IEEE (Institute of Electrical and Electronics Engineers)

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. Vitenskapelig artikkel

Utgiver IEEE (Institute of Electrical and Electronics Engineers)

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. Vitenskapelig artikkel

Utgiver IEEE (Institute of Electrical and Electronics Engineers)

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. Vitenskapelig artikkel

Utgiver IEEE (Institute of Electrical and Electronics Engineers)

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. Vitenskapelig artikkel

Utgiver MDPI

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. Vitenskapelig artikkel

Utgiver MDPI

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. Vitenskapelig artikkel

Utgiver Royal Society of Chemistry (RSC)

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. Vitenskapelig artikkel

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. Vitenskapelig foredrag

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. Vitenskapelig artikkel

Utgiver Pergamon Press

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

Arnt-Børre Salberg; Michael Christian Kampffmeyer; Trends in deep learning 2023. Vitenskapelig foredrag

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

Michael Christian Kampffmeyer; Deep Clustering 2023. Vitenskapelig foredrag

Michael Christian Kampffmeyer; Deep Multi-view Clustering 2023. Vitenskapelig foredrag

Michael Christian Kampffmeyer; Learning from limited labelled data for medical image segmentation 2023. Vitenskapelig foredrag

Michael Christian Kampffmeyer; Self-Explainable Deep Learning 2023. Vitenskapelig foredrag

Michael Christian Kampffmeyer; UiT Machine Learning Group 2023. Vitenskapelig foredrag

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

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

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. Vitenskapelig foredrag

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. Vitenskapelig artikkel

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; 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. Vitenskapelig artikkel

Utgiver Elsevier

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. Vitenskapelig artikkel

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. Vitenskapelig artikkel

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. Vitenskapelig artikkel

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. Vitenskapelig artikkel

Utgiver Elsevier

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. Vitenskapelig artikkel

Utgiver Springer

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. Vitenskapelig artikkel

Utgiver Taylor & Francis

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

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

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

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

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

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. Fagartikkel

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. Vitenskapelig artikkel

Utgiver Oxford University Press

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

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. Vitenskapelig artikkel

Utgiver Taylor & Francis

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. Vitenskapelig artikkel

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, (ISSN 0196-2892 1558-0644 ), doi: https://doi.org/10.1109/TGRS.2021.3056196 , 2021. Vitenskapelig artikkel

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. Vitenskapelig artikkel

Utgiver Institute of Electrical and Electronics Engineers (IEEE)

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

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. Vitenskapelig artikkel

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

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

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. Vitenskapelig artikkel

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. Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

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. Vitenskapelig artikkel

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. Vitenskapelig artikkel

Utgiver Elsevier

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

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. Vitenskapelig artikkel

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. Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

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. Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

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. Vitenskapelig artikkel

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. Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

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. Vitenskapelig foredrag

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

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

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. Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

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. Vitenskapelig artikkel

Utgiver Pergamon Press

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. Vitenskapelig artikkel

Utgiver Elsevier

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. Vitenskapelig artikkel

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. Vitenskapelig artikkel

Utgiver Elsevier

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. Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

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. Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

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. Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

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

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. Vitenskapelig artikkel

Utgiver Institute of Electrical and Electronics Engineers (IEEE)

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. Vitenskapelig foredrag

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. Vitenskapelig foredrag

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

Utgiver Norsk Regnesentral