Kristoffer Wickstrøm,
Eirik Agnalt Østmo,
Keyur Radiya,
Karl Øyvind Mikalsen,
Michael Kampffmeyer,
Robert Jenssen
:
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images
Computerized Medical Imaging and Graphics 2023
ARKIV /
DOI
Changkyu Choi,
Michael Kampffmeyer,
Robert Jenssen,
Nils Olav Handegard,
Arnt-Børre Salberg
:
Deep Semisupervised Semantic Segmentation in Multifrequency Echosounder Data
IEEE Journal of Oceanic Engineering 2023
ARKIV /
DOI
Kristoffer Wickstrøm,
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Ahcene Boubekki,
Karl Øyvind Mikalsen,
Michael Kampffmeyer
m.fl.:
RELAX: Representation Learning Explainability
International Journal of Computer Vision 2023
ARKIV /
DOI
Kristoffer Wickstrøm,
Sigurd Eivindson Løkse,
Michael Kampffmeyer,
Shujian Yu,
José C. Príncipe,
Robert Jenssen
:
Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy
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 2023
DOI
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 2023
Daniel Johansen Trosten,
Rwiddhi Chakraborty,
Sigurd Eivindson Løkse,
Kristoffer Wickstrøm,
Robert Jenssen,
Michael Kampffmeyer
:
Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings
Computer Vision and Pattern Recognition 2023
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 2023
Kristoffer Wickstrøm,
Michael Kampffmeyer,
Karl Øyvind Mikalsen,
Robert Jenssen
:
Mixing up contrastive learning: Self-supervised representation learning for time series
Pattern Recognition Letters 2022
ARKIV /
DOI
Rogelio Andrade Mancisidor,
Michael Kampffmeyer,
Kjersti Aas,
Robert Jenssen
:
Generating customer's credit behavior with deep generative models
Knowledge-Based Systems 2022
ARKIV /
DOI
Stine Hansen,
Srishti Gautam,
Robert Jenssen,
Michael Kampffmeyer
:
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels
Luigi Tommaso Luppino,
Mads Adrian Hansen,
Michael Kampffmeyer,
Filippo Maria Bianchi,
Gabriele Moser,
Robert Jenssen
m.fl.:
Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images
IEEE Transactions on Neural Networks and Learning Systems 12. mai 2022
DOI
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 2022
DOI
Huamin Ren,
Xiaomeng Su,
Robert Jenssen,
Jingyue Li,
Stian Normann Anfinsen
:
Attention-guided Temporal Convolutional Network for Non-intrusive Load Monitoring
IEEE (Institute of Electrical and Electronics Engineers) 2022
ARKIV /
DOI
Shujian Yu,
Francesco Alesiani,
Wenzhe Yin,
Robert Jenssen,
Jose C. Principe
:
Principle of Relevant Information for Graph Sparsification
Proceedings of Machine Learning Research (PMLR) 2022
FULLTEKST /
DOI
Kristoffer Wickstrøm,
Juan Emmanuel Johnson,
Sigurd Eivindson Løkse,
Gusatu Camps-Valls,
Karl Øyvind Mikalsen,
Michael Kampffmeyer
m.fl.:
The Kernelized Taylor Diagram
Communications in Computer and Information Science 2022
ARKIV /
DOI
Suaiba Amina Salahuddin,
Stine Hansen,
Srishti Gautam,
Michael Kampffmeyer,
Robert Jenssen
:
A self-guided anomaly detection-inspired few-shot segmentation network
CEUR Workshop Proceedings 2022
ARKIV
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
Srishti Gautam,
Ahcene Boubekki,
Stine Hansen,
Suaiba Amina Salahuddin,
Robert Jenssen,
Marina Marie-Claire Hohne
m.fl.:
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model
Advances in Neural Information Processing Systems 2022
DOI
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 2022
DOI
Ahcene Boubekki,
Jonas Nordhaug Myhre,
Luigi Tommaso Luppino,
Karl Øyvind Mikalsen,
Arthur Revhaug,
Robert Jenssen
:
Clinically relevant features for predicting the severity of surgical site infections
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Karl Øyvind Mikalsen,
Michael Kampffmeyer,
Robert Jenssen
:
RELAX: Representation Learning Explainability
2022
Kristoffer Knutsen Wickstrøm,
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Karl Øyvind Mikalsen,
Michael Kampffmeyer,
Robert Jenssen
:
RELAX: Representation Learning Explainability
2022
Daniel Johansen Trosten,
Kristoffer Wickstrøm,
Shujian Yu,
Sigurd Eivindson Løkse,
Robert Jenssen,
Michael Kampffmeyer
:
Deep Clustering with the Cauchy-Schwarz Divergence
2022
Robert Jenssen
:
Pasientnær kunstig intelligens
2022
Robert Jenssen
:
Visual Intelligence and environmental monitoring
2022
Robert Jenssen
:
Towards XAI and Visual Intelligence for health
2022
Robert Jenssen
:
Visual Intelligence advances deep learning research towards innovations
2022
Robert Jenssen
:
Women in AI panel debate
2022
Robert Jenssen
:
Towards XAI and Visual Intelligence for health
2022
Robert Jenssen
:
Learning from limited data
2022
Robert Jenssen
:
Machine Learning Research, AI Technology and Ethical Considerations
2022
Robert Jenssen
:
Visual Intelligence and graph neural networks
2022
Robert Jenssen
:
Mot framtidas helsevesen med kunstig intelligens
2022
Robert Jenssen
:
Kunstig intelligens-utdanninger for helse ved UiT
2022
Robert Jenssen
:
Paneldebatt framtidas helsevesen med AI
2022
Robert Jenssen
:
Visual Intelligence for medical image analysis
2022
Robert Jenssen
:
Presentation of SFI Visual Intelligence
2022
Robert Jenssen
:
Etikk og AI
2022
Robert Jenssen
:
Centre for Research-based Innovation Visual Intelligence and the General Electric Vingmed Ultrasound Collaboration
2022
Robert Jenssen
:
Computer vision for power line monitoring
2022
Robert Jenssen
:
An introduction to self-supervised learning with examples of use cases in few-shot learning and medical image analysis
2022
Robert Jenssen
:
Innovasjon i Visual Intelligence
2022
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
Srishti Gautam,
Marina Marie-Claire Hohne,
Stine Hansen,
Robert Jenssen,
Michael Kampffmeyer
:
Artifact Detection with Prototypical Relevance Propagation
2022
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
Samuel Kuttner,
Luigi Tommaso Luppino,
Kristoffer Wickstrøm,
Nils Thomas Doherty Midtbø,
Seyed Esmaeil Dorraji,
Ana Oteiza
m.fl.:
Deep learning derived input function in dynamic 18F-FDG PET imaging of mice
2022
Kristoffer Wickstrøm,
Eirik Agnalt Østmo,
Karl Øyvind Mikalsen,
Michael Kampffmeyer,
Robert Jenssen
:
Explaining representations for medical image retrieval
2022
Kristoffer Wickstrøm,
Juan Emmanuel Johnson,
Sigurd Eivindson Løkse,
Gusatu Camps-Valls,
Karl Øyvind Mikalsen,
Michael Kampffmeyer
m.fl.:
The Kernelized Taylor Diagram
2022
Changkyu Choi,
Shujian Yu,
Michael Kampffmeyer,
Arnt-Børre Salberg,
Nils Olav Handegard,
Suaiba Amina Salahuddin
m.fl.:
Explaining Marine Acoustic Target Classification in Multi-channel Echosounder Data using Self-attention Mask, Information-Bottleneck, and Mask Prior
2022