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

New Visual Intelligence paper accepted to NeurIPS

September 15, 2022
By
Srishti Gautam, Ahcene Boubekki, Stine Hansen, Suaiba Salahuddin, Robert Jenssen, Marina Höhne, Michael Kampffmeyer

Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks

July 1, 2022
By
Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg

All publications

ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model

By authors:

Srishti Gautam, Ahcene Boubekki, Stine Hansen, Suaiba Salahuddin, Robert Jenssen, Marina Höhne, Michael Kampffmeyer

Published in:

NeurIPS 2022

on

September 15, 2022

ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design

By authors:

Xujie Zhang, Yu Sha, Michael Kampffmeyer, Zhenyu Xie, Zequn Jie, Chengwen Huang, Jianqing Peng, Xiaodan Liang

Published in:

ACM Multimedia (ACM MM 2022)

on

August 11, 2022

Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks

By authors:

Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg

Published in:

International Journal of Remote Sensing, 2022

on

July 1, 2022

Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images

By authors:

Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu

Published in:

International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2022)

on

June 30, 2022

Principle of Relevant Information for Graph Sparsification

By authors:

Shujian Yu, Francesco Alesiani, Wenzhe Yin, Robert Jenssen and Jose C. Principe

Published in:

Conference on Uncertainty in Artificial Intelligence (UAI) 2022

on

May 20, 2022

Mitral Annulus Segmentation and Anatomical Orientation Detection in TEE Images Using Periodic 3D CNN

By authors:

Børge Solli Andreassen, David Völgyes, Eigil Samset, Anne H. Schistad Solberg

Published in:

IEEE Access, Engineering in Medicine and Biology Section

on

May 10, 2022

Toward Scalable and Unified Example-Based Explanation and Outlier Detection

By authors:

Penny Chong, Ngai-Man Cheung, Yuval Elovici, Alexander Binder

Published in:

IEEE Transactions on Image Processing, vol. 31, pp. 525-540, 2022

on

March 11, 2022

M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining

By authors:

Xiao Dong, Xunlin Zhan, Yangxin Wu, Yunchao Wei, Michael C. Kampffmeyer, Xiaoyong Wei, Minlong Lu, Yaowei Wang, Xiaodan Liang

Published in:

Conference on Computer Vision and Pattern Recognition (CVPR), 2022

on

March 3, 2022

Data-Driven Robust Control Using Reinforcement Learning

By authors:

Phuong D. Ngo, Miguel Tejedor and Fred Godtliebsen

Published in:

Appl. Sci. 2022, 12(4), 2262

on

February 21, 2022

A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images

By authors:

Nikita Shvetsov, Morten Grønnesby, Edvard Pedersen, Kajsa Møllersen, Lill-Tove Rasmussen Busund, Ruth Schwienbacher, Lars Ailo Bongo, Thomas K. Kilvaer

Published in:

Cancers 2022, 14, 2974

on

February 14, 2022

Other publications

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