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

Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction

By authors:

Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba A. Salahuddin, Kristoffer Wickstrøm, Elisabeth Wetzer, Robert Jenssen, Maik Stille, Michael Kampffmeyer

Published in:

Medical Image Computing and Computer Assisted Intervention – MICCAI 2025.

on

September 17, 2025

Joint despeckling and thermal noise compensation: application to Sentinel-1 images of the Arctic

By authors:

Inès Meraoumia, Debanshu Ratha, Emanuele Dalsasso, Johannes Lohse, Florence Tupin, Andrea Marinoni, Loic Denis

Published in:

IEEE Transactions on Geoscience and Remote Sensing, vol. 63, pp. 1-12, 2025

on

September 16, 2025

Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders

By authors:

Rogelio A Mancisidor, Robert Jenssen, Shujian Yu, Michael Kampffmeyer

Published in:

International Conference on Machine Learning (ICLM) 2025

on

August 13, 2025

Quantifying uncertainty in foraminifera classification: How deep learning methods compare to human experts

By authors:

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

Published in:

Artificial Intelligence in Geosciences

on

July 16, 2025

Self-Organizing Visual Prototypes for Non-Parametric Representation Learning

By authors:

Thalles Silva, Helio Pedrini and Adín Ramírez Rivera

Published in:

Forty-Second International Conference on Machine Learning (ICML), Vancouver, Canada 13-19 July, 2025

on

July 13, 2025

Leveraging Foundation Model Adapters to Enable Robust and Semantic Underwater Exploration

By authors:

Changkyu Choi, Arangan Subramaniam, Nils Olav Handegard, Ali Ramezani-Kebrya and Robert Jenssen

Published in:

Proceedings of the Symposium of the Norwegian AI Society 2025, CEUR Workshop Proceedings ( ISSN 1613-0073)

on

June 17, 2025

Pixel-Level Predictions with Embedded Lookup Tables

By authors:

Marius Aasan, Adín Ramírez Rivera

Published in:

Proceedings of the Symposium of the Norwegian AI Society 2025, CEUR Workshop Proceedings ( ISSN 1613-0073)

on

June 17, 2025

Assessing the Efficacy of Multi-task Learning in Mammographic Density Classification: A Study on Class Imbalance and Model Performance

By authors:

Suaiba A. Salahuddin, Elisabeth Wetzer, Kristoffer Wickstrøm, Solveig Thrun, Michael Kampffmeyer and Robert Jenssen

Published in:

Lecture Notes in Computer Science (LNCS) 2025 ;Volum 15726.

on

June 16, 2025

AdaptCMVC: Robust Adaption to Incremental Views in Continual Multi-view Clustering

By authors:

Jing Wang, Songhe Feng, Kristoffer Wickstrøm, Michael Kampffmeyer

Published in:

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 10285-10294, 2025

on

June 10, 2025

Interactive Injectite Mapping with Minimal Training Data using Self-Supervised Learning

By authors:

A. Waldeland, T.J.L. Forgaard, A. Ordonez, D. Wade and A.J. Bugge

Published in:

86th EAGE Annual Conference & Exhibition, Jun 2025, Volume 2025, p.1 - 5

on

June 2, 2025

Other publications

annual reports