Samuel Kuttner,
Luigi Tommaso Luppino,
Laurence Convert,
Otman Sarrhini,
Roger Lecomte,
Michael Christian Kampffmeyer
m.fl.:
Deep learning derived input function in dynamic [18F]FDG PET imaging of mice
Frontiers in Nuclear Medicine 2024
DOI
Harald Lykke Joakimsen,
Iver Martinsen,
Luigi Tommaso Luppino,
Andrew McDonald,
Scott Hosking,
Robert Jenssen
:
Interrogating Sea Ice Predictability with Gradients
IEEE Geoscience and Remote Sensing Letters 2024
DOI
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Robert Jenssen,
Michael Christian Kampffmeyer
:
Leveraging tensor kernels to reduce objective function mismatch in deep clustering
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 2024
DOI
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 2023
ARKIV /
DOI
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
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
Rogelio Andrade Mancisidor,
Michael Christian Kampffmeyer,
Kjersti Aas,
Robert Jenssen
:
Discriminative multimodal learning via conditional priors in generative models
Kristoffer Vinther Olesen,
Ahcene Boubekki,
Michael Christian Kampffmeyer,
Robert Jenssen,
Anders Nymark Christensen,
Sune Hørlück
m.fl.:
A Contextually Supported Abnormality Detector for Maritime Trajectories
Journal of Marine Science and Engineering (JMSE) 2023
ARKIV /
DOI
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
ARKIV /
DOI
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
ARKIV /
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 22. august 2023
ARKIV /
DATA /
DOI
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
Ane Blazquez-Garcia,
Kristoffer Knutsen Wickstrøm,
Shujian Yu,
Karl Øyvind Mikalsen,
Ahcene Boubekki,
Angel Conde
m.fl.:
Selective Imputation for Multivariate Time Series Datasets with Missing Values
IEEE Transactions on Knowledge and Data Engineering 2023
ARKIV /
DOI
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
ARKIV /
DOI
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
ARKIV /
DOI
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,
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
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
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
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
Changkyu Choi,
Michael Christian Kampffmeyer,
Nils Olav Handegard,
Arnt-Børre Salberg,
Robert Jenssen
:
Deep Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data
2023
Robert Jenssen
:
XAI for representation learning
2023
Robert Jenssen
:
Kunstig intelligens i helse
2023
Robert Jenssen
:
En offensiv offentlig politikk for kunstig intelligens i helsetjenesten
2023
Fredrik Emil Aspheim,
Luigi Tommaso Luppino,
Michael Christian Kampffmeyer,
Robert Jenssen,
Rune Sundset,
Akos Samuel Kuttner
:
Interpretable deep learning model for input function estimation in small-animal 18F-FDG PET imaging
2023
Robert Jenssen
:
Deltaker i podcasten KA i KI
08. desember 2023
Robert Jenssen
:
NRK-intervju Arendalsuka
16. august 2023
Robert Jenssen
:
Kunstig intelligens – Hva er det? Hvor kan det (mis)brukes
2023
Robert Jenssen
:
Kunstig intelligens i fremtidens helsetjenester
30. september 2023
Robert Jenssen
:
Information Theory Meets Deep Learning
2023
Robert Jenssen
:
Information theoretic approaches: To clustering, graph neural networks and for investigating the dynamics of learning
2023
Robert Jenssen
:
A major Norwegian hub for AI research in health
2023
Robert Jenssen
:
Self-supervised learning with XAI
2023
Robert Jenssen
:
XAI for representation learning
2023
Robert Jenssen
:
Deep learning in image analysis, graphs, and a new measure of statistical dependency between graphs
2023
Robert Jenssen
:
On representation learning with information theoretic criteria and a new method for representation learning interpretability
2023
Robert Jenssen
:
Stortinget: Kunstig intelligens i helse
2023
Harald Lykke Joakimsen,
Iver Martinsen,
Luigi Tommaso Luppino,
Robert Jenssen
:
"Explainable" IceNet with backpropagated gradients
2023
Fredrik Emil Aspheim,
Samuel Kuttner,
Luigi Tommaso Luppino,
Rune Sundset,
Michael Christian Kampffmeyer,
Robert Jenssen
:
Deep learning derived input-function in dynamic PET-imaging
2023
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
Robert Jenssen
:
Pasientnær kunstig intelligens
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
Robert Jenssen
:
Etikk og AI
2022
Robert Jenssen
:
Presentation of SFI Visual Intelligence
2022
Robert Jenssen
:
Paneldebatt framtidas helsevesen med AI
2022
Robert Jenssen
:
Mot framtidas helsevesen med kunstig intelligens
2022