Michael Christian Kampffmeyer
Michael Christian Kampffmeyer
Professor in Machine Learning, UiT the Arctic University of Norway, Tromsø
Verifisert e-postadresse på post.uit.no - Startside
Sitert av
Sitert av
Semantic segmentation of small objects and modeling of uncertainty in urban remote sensing images using deep convolutional neural networks
M Kampffmeyer, AB Salberg, R Jenssen
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
Recurrent Neural Networks for Short-Term Load Forecasting: An Overview and Comparative Analysis
FM Bianchi, E Maiorino, MC Kampffmeyer, A Rizzi, R Jenssen
Springer, 2017
Rethinking knowledge graph propagation for zero-shot learning
M Kampffmeyer, Y Chen, X Liang, H Wang, Y Zhang, EP Xing
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps
K Wickstrøm, M Kampffmeyer, R Jenssen
Medical Image Analysis 60, 101619, 2020
Reconsidering Representation Alignment for Multi-view Clustering
DJ Trosten, S Løkse, R Jenssen, M Kampffmeyer
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
Dense dilated convolutions’ merging network for land cover classification
Q Liu, M Kampffmeyer, R Jenssen, AB Salberg
IEEE Transactions on Geoscience and Remote Sensing 58 (9), 6309-6320, 2020
Unsupervised domain adaptation for automatic estimation of cardiothoracic ratio
N Dong, M Kampffmeyer, X Liang, Z Wang, W Dai, E Xing
International Conference on Medical Image Computing and Computer-Assisted …, 2018
Deep image translation with an affinity-based change prior for unsupervised multimodal change detection
LT Luppino, M Kampffmeyer, FM Bianchi, G Moser, SB Serpico, ...
IEEE Transactions on Geoscience and Remote Sensing, 2021
Code-aligned autoencoders for unsupervised change detection in multimodal remote sensing images
LT Luppino, MA Hansen, M Kampffmeyer, FM Bianchi, G Moser, ...
IEEE Transactions on Neural Networks and Learning Systems 35 (1), 60-72, 2022
Mixing up contrastive learning: Self-supervised representation learning for time series
K Wickstrøm, M Kampffmeyer, KØ Mikalsen, R Jenssen
Pattern Recognition Letters 155, 54-61, 2022
Learning representations of multivariate time series with missing data
FM Bianchi, L Livi, KØ Mikalsen, M Kampffmeyer, R Jenssen
Pattern Recognition 96, 106973, 2019
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels
S Hansen, S Gautam, R Jenssen, M Kampffmeyer
Medical Image Analysis 78, 102385, 2022
ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation
M Kampffmeyer, N Dong, X Liang, Y Zhang, EP Xing
IEEE Transactions on Image Processing 28 (5), 2518-2529, 2018
Deep divergence-based approach to clustering
M Kampffmeyer, S Løkse, FM Bianchi, L Livi, AB Salberg, R Jenssen
Neural Networks 113, 91-101, 2019
M3D-VTON: A Monocular-to-3D Virtual Try-On Network
F Zhao, Z Xie, M Kampffmeyer, H Dong, S Han, T Zheng, T Zhang, ...
ICCV 2021, 2021
Urban Land Cover Classification With Missing Data Modalities Using Deep Convolutional Neural Networks
M Kampffmeyer, AB Salberg, R Jenssen
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018
Deep generative models for reject inference in credit scoring
RA Mancisidor, M Kampffmeyer, K Aas, R Jenssen
Knowledge-Based Systems 196, 105758, 2020
Uncertainty Modeling and Interpretability in Convolutional Neural Networks for Polyp Segmentation
K Wickstrøm, M Kampffmeyer, R Jenssen
2018 IEEE 28th International Workshop on Machine Learning for Signal …, 2018
Dtr-gan: Dilated temporal relational adversarial network for video summarization
Y Zhang, M Kampffmeyer, X Zhao, M Tan
Proceedings of the ACM Turing Celebration Conference-China, 89, 2019
Query-Conditioned Three-Player Adversarial Network for Video Summarization
Y Zhang, M Kampffmeyer, X Liang, M Tan, EP Xing
British Machine Vision Conference (BMVC), 2018, 2018
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