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 papers

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

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

A Generalized Geodesic Distance-Based Approach for Analysis of SAR Observations Across Polarimetric Modes

By authors:

Debanshu Ratha, Andrea Marinoni and Torbjørn Eltoft

Published in:

IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-16, 2023

on

December 23, 2022

Federated Partially Supervised Learning With Limited Decentralized Medical Images

By authors:

Dong, Nanqing; Kampffmeyer, Michael; Voiculescu, Irina; Xing, Eric

Published in:

IEEE Transactions on Medical Imaging 2023 ;Volum 42.(7) s.1944-1954

on

December 20, 2022

Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning

By authors:

Huang, Zaiyu; Li, Hanhui; Xie, Zhenyu; Kampffmeyer, Michael; Cai, Qingling; Liang, Xiaodan.

Published in:

Advances in Neural Information Processing Systems 2022 s. -

on

November 25, 2022

A self-guided anomaly detection-inspired few-shot segmentation network

By authors:

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

Published in:

CEUR Workshop Proceedings 2022, Volum 3271.

on

November 13, 2022

Gated information bottleneck for generalization in sequential environments

By authors:

Francesco Alesiani, Shujian Yu and Xi Yu

Published in:

Knowledge and Information Systems (KAIS)

on

October 31, 2022

Other publications

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