Deep learning in earth observation

Monitoring and prediction of hazard risks and streamlining of aerial surveys.

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 hazard risks such as potential oil spills at sea.

For earth observation the planned innovations are related to improved methods for monitoring and prediction of hazard risks and for surveying and mapping ground and sea from air through exploitation of remote sensing images from satellites, aircrafts and drones. 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. Modelling of contextual information can be important to enhance the performance, e.g. if we aim to delineate a road network, we want the roads to be connected. Since the CNNs are inherently pixel based, major modifications are needed to integrate such information.

These are some of the challenges Visual Intelligence is addressing.

Related news

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.