SAMBA

Statistical Analysis, Machine Learning and Image Analysis - SAMBA

The SAMBA department has comprehensive theoretical and practical knowledge in the fields of statistics, machine learning and image analysis. We are one of Europe's largest and most competent groups within applied statistics and statistical-matematical modelling. We cover a broad spectrum of methods and are a world leader in some of these areas. The appropriate choice of method for the various problems is thus one of our strengths. Many calculations involve uncertainty and the accurate calculation of this quantity is an important speciality.

Research areas

Statistics for climate and environment

Our research within statistics for climate and environment is a mixture of applied, problem-driven projects and fundamental research eligible for publication in scientific journals.

Statistics for finance, insurance and commodity markets

We use statistical methods to quantify all kinds of risk in the banking, insurance and commodity markets. We work a lot with models related to Basel II and Solvency II and have developed a large number of systems related to trading and risk management for various power companies.

Statistics for marine resources and health

We cover a wide range of applications within the areas marine resources and health.

Statistics for technology and industry

We cover a wide range of applications including forecasting, time series analysis, network modelling, optimal delivery, logistics, optimal steering of industry processes, reliability analysis, cost surveys and analysis of very large data sets.

Earth observation

We do research and development of methodologies for analysis of digital remote sensing data from satellites and aircrafts. Application areas include environmental monitoring, climate change monitoring, environmental emergency detection, natural resource mapping and map revision.

Image Analysis and Machine Learning

We have extensive knowledge in the fields of image analysis and machine learning. Object extraction, characterization and recognition from images are central for many of these applications. Another central theme is the analysis of sequences of data, including motion detection and characterization.

Big Insight

This center for research-based-innovation is funded by the Research Council of Norway. Big Insight produces innovative solutions for key challenges facing our consortium of private, public and research partners, by developing original statistical and machine learning methodologies.

Last 5 scientific articles

Reksten, Jarle Hamar; Salberg, Arnt-Børre. Estimating Traffic in Urban Areas from Very-High Resolution Aerial Images. International Journal of Remote Sensing (ISSN 0143-1161). 42(3) pp 865-883. doi: 10.1080/01431161.2020.1815891. 2021.

Brødholt, Elin Therese; Günther, Clara-Cecilie; Gautvik, Kaare M; Sjøvold, Torstein; Holck, Per. Bone mineral density through history: Dual-energy X-ray absorptiometry in archaeological populations of Norway. Journal of Archaeological Science: Reports (ISSN 2352-409X). 36 2021.

Günther, Clara-Cecilie; Gautvik, Kaare M; Holck, Per; Sjøvold, Torstein. Bone mineral density through history: Dual-energy X-ray absorptiometry in archaeological populations of Norway. Journal of Archaeological Science: Reports (ISSN 2352-409X). doi: 10.1016/j.jasrep.2021.102792. 2021.

Aldrin, Magne Tommy; Huseby, Ragnar Bang; Jensen, Britt Bang; Jansen, Mona Dverdal. Evaluating effects of different control strategies for Infectious Salmon Anaemia (ISA) in marine salmonid farming by scenario simulation using a disease transmission model. Preventive Veterinary Medicine (ISSN 0167-5877). 2021.

Jensen, Britt Bang; Dean, Katharine Rose; Huseby, Ragnar Bang; Aldrin, Magne Tommy; Qviller, Lars. Realtime simulations of transmission of Pancreas Disease (PD) in Norwegian salmonid farming for disease control purposes. Epidemics (ISSN 1755-4365). 2021.

Publications in 2021, 2020, 2019, 2018, 2017, earlier years