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

AI matches human experts in classifying microscopic organisms

July 16, 2025
By
Iver Martinsen, Steffen Aagaard Sørensen, Samuel Ortega, Fred Godtliebsen, Miguel Tejedor, Eirik Myrvoll-Nilsen

Visual Data Diagnosis and Debiasing with Concept Graphs

September 26, 2024
By
Chakraborty, Rwiddhi; Wang, Yinong; Gao, Jialu; Zheng, Runkai; Zhang, Cheng; De la Torre, Fernando

All publications

Distributed extra-gradient with optimal complexity and communication guarantees

By authors:

Ali Ramezani-Kebrya, Kimon Antonakopoulos, Igor Krawczuk, Justin Deschenaux, Volkan Cevher

Published in:

International Conference on Learning Representations ICLR 2023

on

May 1, 2023

Automatic Identification of Chemical Moieties

By authors:

Jonas Lederer, Michael Gastegger, Kristof T. Schütt, Michael Kampffmeyer, Klaus-Robert Müller, and Oliver T. Unke

Published in:

Physical Chemistry Chemical Physics 2023

on

April 27, 2023

This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation

By authors:

Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer

Published in:

Pattern Recognition, Volume 136, 2023

on

April 1, 2023

Predicting Regions of Local Recurrence in Glioblastomas Using Voxel-Based Radiomic Features of Multiparametric Postoperative MRI

By authors:

Cepeda, Santiago and Luppino, Luigi Tommaso and Pérez-Núñez, Angel and Solheim, Ole and García-García, Sergio and Velasco-Casares, María and Karlberg, Anna and Eikenes, Live and Sarabia, Rosario and Arrese, Ignacio and Zamora, Tomás and Gonzalez, Pedro and Jiménez-Roldán, Luis and Kuttner, Samuel

Published in:

Cancers. 2023; 15(6):1894.

on

March 22, 2023

RELAX: Representation Learning Explainability

By authors:

Wickstrøm, Kristoffer; Trosten, Daniel Johansen; Løkse, Sigurd Eivindson; Boubekki, Ahcene; Mikalsen, Karl Øyvind; Kampffmeyer, Michael; Jenssen, Robert

Published in:

International Journal of Computer Vision 2023 ;Volum 131.(6) s.1584-1610

on

March 11, 2023

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

By authors:

Daniel J. Trosten*, Rwiddhi Chakraborty*, Sigurd Løkse, Kristoffer Knutsen Wickstrøm, Robert Jenssen, Michael Kampffmeyer (* indicates equal contribution)

Published in:

CVPR 2023

on

March 6, 2023

On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering

By authors:

Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael Kampffmeyer.

Published in:

Computer Vision and Pattern Recognition 2023 s.23976-23985

on

March 6, 2023

SAR and Passive Microwave Fusion Scheme: A Test Case on Sentinel-1/AMSR-2 for Sea Ice Classification

By authors:

Khachatrian, Eduard; Dierking, Wolfgang; Chlaily, Saloua; Eltoft, Torbjørn; Dinessen, Frode; Hughes, Nick; Marinoni, Andrea.

Published in:

Geophysical Research Letters 2023 ;Volum 50.(4) s.1-7

on

February 14, 2023

The Kernelized Taylor Diagram

By authors:

Kristoffer Wickstrøm, Juan Emmanuel Johnson, Sigurd Eivindson Løkse, Gusatu Camps-Valls, Karl Øyvind Mikalsen, Michael Kampffmeyer, and Robert Jenssen

Published in:

NAIS 2022 Communications in Computer and Information Science, vol 1650. Springer

on

February 2, 2023

Deep Semisupervised Semantic Segmentation in Multifrequency Echosounder Data

By authors:

Changkyu Choi, Michael Kampffmeyer, Nils Olav Handegard, Arnt-Børre Salberg and Robert Jenssen

Published in:

IEEE Journal of Oceanic Engineering

on

February 1, 2023

Other publications

annual reports