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

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

Modular Superpixel Tokenization in Vision Transformers

August 28, 2024
By
Marius Aasan, Odd Kolbjørnsen, Anne Schistad Solberg, Adín Ramirez Rivera

All publications

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

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

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

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

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

Deep Semi supervised Semantic Segmentation in Multifrequency Echosounder Data

By authors:

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

Published in:

IEEE Journal of Oceanic Engineering 2023 ;Volum 48.(2) s.384-400

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

Other publications

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