Scientific publications

At Visual Intelligence we work across our innovation areas to extract knowledge from large volumes of visual data more efficiently through automatic and intelligent data analysis. The work to address the core research challenges in deep learning: working with limited training data, utilizing context and dependencies, providing explainability, confidence and uncertainty, are important in all the innovation areas.

Featured blog posts

Interrogating Sea Ice Predictability With Gradients

February 14, 2024
By
Joakimsen, H. L., Martinsen I., Luppino, L. T., McDonald, A., Hosking, S., and Jenssen, R.

Merging clustering into deep supervised neural network

June 4, 2023
By
Durgesh Singh, Ahcéne Boubekki, Robert Jenssen, Michael C. Kampffmeyer

All publications

Using Deep Learning Methods for Segmenting Polar Mesospheric Summer Echoes

By authors:

Domben, Erik Seip; Sharma, Puneet; Mann, Ingrid

Published in:

Remote Sensing 2023 ;Volum 15.(17) Suppl. 4291. s.1-23

on

August 31, 2023

Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings.

By authors:

Trosten, Daniel Johansen; Chakraborty, Rwiddhi; Løkse, Sigurd Eivindson; Wickstrøm, Kristoffer; Jenssen, Robert; Kampffmeyer, Michael.

Published in:

Computer Vision and Pattern Recognition 2023 s.7527-7536

on

August 22, 2023

DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment

By authors:

Xujie Zhang, Binbin Yang, Michael C. Kampffmeyer, Wenqing Zhang, Shiyue Zhang, Guansong Lu, Liang Lin, Hang Xu, Xiaodan Liang

Published in:

IEEE International Conference on Computer Vision (ICCV) 2023

on

August 20, 2023

Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos,

By authors:

Haoyuan Li, Haoye Dong, Hanchao Jia, Dong Huang, Michael C. Kampffmeyer, Liang Lin, Xiaodan Liang

Published in:

ICCV 2023

on

August 20, 2023

ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement

By authors:

Hansen, Stine; Gautam, Srishti; Salahuddin, Suaiba Amina; Kampffmeyer, Michael Christian; Jenssen, Robert

Published in:

Medical Image Analysis 2023 ;Volum 89

on

August 2, 2023

Reverberation Suppression in Echocardiography Using a Causal Convolutional Neural Network

By authors:

Jahren, Tollef Struksnes; Sørnes, Anders Rasmus; Dénarié, Bastien Emmanuel; Steen, Erik; Bjåstad, Tore Grüner; Solberg, Anne H Schistad

Published in:

IEEE Access, vol. 11, pp. 67922-67937, 2023

on

July 4, 2023

SuperCM: Revisiting Clustering for Semi-Supervised Learning

By authors:

Durgesh Singh, Ahcéne Boubekki, Robert Jenssen, Michael C. Kampffmeyer

Published in:

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

on

June 4, 2023

THE FIRST PATHLOSS RADIO MAP PREDICTION CHALLENGE

By authors:

Cagkan Yapar , Fabian Jaensch, Ron Levie‡ Gitta Kutyniok, Giuseppe Caire

Published in:

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |

on

June 4, 2023

Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy

By authors:

Wickstrøm, Kristoffer; Løkse, Sigurd Eivindson; Kampffmeyer, Michael; Yu, Shujian; Príncipe, José C.; Jenssen, Robert.

Published in:

Entropy 2023 ;Volum 25.(6) s.1-21

on

June 3, 2023

Federated Learning under Covariate Shifts with Generalization Guarantees

By authors:

Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher

Published in:

Transactions on Machine Learning Research

on

June 1, 2023

Other publications

annual reports