Earth observation

Monitoring and prediction of objects, hazard risks and streamlining of aerial surveys

Background

Optical images from drones or satellites and data captured by radar sensors from above contain enormous amounts of complex data. They have the potential to reveal valuable information about our planet and its surface that could be used automate terrain mapping or to predict objects and hazard risks such as vessels and potential oil spills at sea.

Main objective

For earth observation the planned innovations aim for improved methods for monitoring and prediction of hazard risks, object detection, and for surveying and mapping ground and sea from air through exploitation of remote sensing images from satellites, aircrafts and drones.

Challenges

Limited and inadequate training data is a general problem in remote sensing. Combination of multi-sensor data (e.g. from optical and radar sensors) and time dependencies is another key challenge. Modelling of contextual information may also enhance the performance, but important contextual issues like integration of physical properties have not yet been addressed.

These are some of the research challenges Visual Intelligence are addressing.

Related news

Paper published in International Journal of Remote Sensing
June 28, 2021

Qinghui Liu, Michael Kampffmeyer, Robert Jenssen and Arnt-Børre Salberg have published their paper Self-constructing graph neural networks to model long-range pixel dependencies for semantic segmentation of remote sensing images in International Journal of Remote Sensing.

Stream our latest seminars
May 27, 2021

Did you miss any of our recent seminars? When we host seminars and events we often record relevant talks and presentations and make them available at our youtube channel. You can access all our content through our "outreach" page.

Annual report 2020
May 20, 2021

SFI Visual Intelligence has published the annual report for 2020. The report is approved by the Visual Intelligence board and available for download as a pdf document under "publicity".

Visual Intelligence Graduate School (VIGS)
May 20, 2021

SFI Visual Intelligence is organizing a graduate school for early career research fellows connected to Visual Intelligence. VIGS aims at connecting research fellows across our different research institutions to build social and professional networks.

Northern Lights Deep Learning Workshop 2021
January 19, 2021

NLDL 2021 will be a digital conference hosted by the UiT Machine Learning Group and Visual Intelligence January 18-20. The program includes a Mini Deep Learning School the 18th and is followed by a tight program the rest of the week.

A new Centre for Research-based Innovation
January 19, 2021

Visual Intelligence will be one of the new SFIs funded by the Research Council of Norway. The center will run over a period of eight years and will form a collaboration between businesses and research institutions in Norway.

Visual Intelligence is officially opened!
January 19, 2021

The official opening of SFI Visual Intelligence was successfully arranged as a digital event today. We are now ready to commence our research and innovation to tackle some of the large challenges in deep learning and AI, along with our partners.

Related projects

New algorithms for vessel and object detection
December 17, 2020
Visual Intelligence collaborates with KSAT to improve existing, and develop new algorithms, for vessel detection and object recognition.
New methods for automatic change detection in aerial images
December 17, 2020
A collaboration with Terratec to develop deep learning methods to automatically detect changes when updating an existing map database.
Oil-spill detection and characterization of thickness
December 9, 2020
Visual Intelligence collaborates with KSAT to develop new models for detecting and characterizing oil spills.