• Unified detection system for automatic, real-time, accurate animal detection in camera trap images from the arctic tundra 

      Thom, Håvard (Master thesis; Mastergradsoppgave, 2017-06-01)
      A more efficient and effective approach for detecting animal species in digital images is required. Every winter, the Climate-ecological Observatory for Arctic Tundra (COAT) project deploys several dozen camera traps in eastern Finnmark, Norway. These cameras capture large volumes of images that are used to study and document the impact of climate changes on animal populations. Currently, the images ...
    • Using machine learning to provide automatic image annotation for wildlife camera traps in the Arctic 

      Thom, Håvard; Bjørndalen, John Markus; Kleiven, Eivind Flittie; Soininen, Eeva M; Killengreen, Siw Turid; Ehrich, Dorothee; Ims, Rolf Anker; Anshus, Otto; Horsch, Alexander (Chapter; Bokkapittel, 2017)
      The arctic tundra is considered the terrestrial biome expected to be most impacted by climate change, with temperatures projected to increase as much as 10 °C by the turn of the century. The Climate-ecological Observatory for Arctic Tundra (COAT) project monitors the climate and ecosystems using several sensor types. We report on results from projects that automate image annotations from two of the ...