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

Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation

By authors:

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

Published in:

IEEE International Symposium on Biomedical Imaging (ISBI) 2022

on

February 1, 2022

Towards robust partially supervised multi-structure medical image segmentation on small-scale data

By authors:

Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Min Xu, Irina Voiculescu and Eric Xing

Published in:

Applied Soft Computing, Volume 114, 2022

on

January 1, 2022

Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN

By authors:

Zhenyu Xie, Zaiyu Huang, Fuwei Zhao, Haoye Dong, Michael Kampffmeyer, Xiaodan Liang

Published in:

Advances in Neural Information Processing Systems 34 pre-proceedings (NeurIPS 2021)

on

December 23, 2021

Machine Learning + Marine Science: Critical Role of Partnerships in Norway

By authors:

Nils Olav Handegard, Line Eikvil, Robert Jenssen, Michael Kampffmeyer, Arnt-Børre Salberg, and Ketil Malde

Published in:

Journal of Ocean Technology 2021

on

October 6, 2021

Semi-supervised target classification in multi-frequency echosounder data

By authors:

Changkyu Choi, Michael Kampffmeyer, Nils Olav Handegard, Arnt-Børre Salberg, Olav Brautaset, Line Eikvil, Robert Jenssen

Published in:

ICES Journal of Marine Science, Volume 78, Issue 7, October 2021, Pages 2615–2627

on

August 12, 2021

Joint optimization of an autoencoder for clustering and embedding

By authors:

Ahcène Boubekki, Michael Kampffmeyer, Ulf Brefeld, Robert Jenssen

Published in:

Machine Learning (2021)

on

June 21, 2021

Self-constructing graph neural networks to model long-range pixel dependencies for semantic segmentation of remote sensing images

By authors:

Qinghui Liu (Brian), Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg

Published in:

International Journal of Remote Sensing

on

June 16, 2021

RadioUNet: Fast Radio Map Estimation With Convolutional Neural Networks

By authors:

Ron Levie , Çagkan Yapar , Gitta Kutyniok, and Giuseppe Caire

Published in:

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 20, NO. 6, JUNE 2021

on

June 6, 2021

Reconsidering Representation Alignment for Multi-view Clustering

By authors:

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

Published in:

CVPR 2021

on

March 13, 2021

Morphological and molecular breast cancer profiling through explainable machine learning

By authors:

Alexander Binder, Michael Bockmayr, Miriam Hägele, Stephan Wienert, Daniel Heim, Katharina Hellweg, Masaru Ishii, Albrecht Stenzinger, Andreas Hocke, Carsten Denkert, Klaus-Robert Müller & Frederick Klauschen

Published in:

Nature Machine Intelligence volume 3, pages 355–366 (2021)

on

March 8, 2021

Other publications

annual reports