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dc.contributor.authorThom, Håvard
dc.contributor.authorBjørndalen, John Markus
dc.contributor.authorKleiven, Eivind Flittie
dc.contributor.authorSoininen, Eeva M
dc.contributor.authorKillengreen, Siw Turid
dc.contributor.authorEhrich, Dorothee
dc.contributor.authorIms, Rolf Anker
dc.contributor.authorAnshus, Otto
dc.contributor.authorHorsch, Alexander
dc.date.accessioned2023-05-05T12:21:23Z
dc.date.available2023-05-05T12:21:23Z
dc.date.issued2017
dc.description.abstractThe 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 camera traps used by COAT: an artificial tunnel under the snow for capturing information about small mammals, and an open-air camera trap using bait that captures information of a range of larger sized birds and mammals. These traps currently produce over two million pictures per year. <p> <p>We have developed and trained several Convolutional Neural Network (CNN) models to automate annotation of images from these camera traps. Results show that we get a high accuracy: 97.84% for tunnel traps, and 94.1% for bait traps. This exceeds previous state of the art in animal identification on camera trap images, and is at a level where we can already relieve experts from manual annotation of images.en_US
dc.descriptionSource at <a href=https://hdl.handle.net/10037/26504>https://hdl.handle.net/10037/26504</a>.en_US
dc.identifier.citationThom H, Bjørndalen JM, Kleiven EF, Soininen EM, Killengreen St, Ehrich D, Ims RA, Anshus O, Horsch A: Using machine learning to provide automatic image annotation for wildlife camera traps in the Arctic. In: Melbye H. Proceedings from the 42nd annual conference of the International Lung Sound Association, ILSA 2017, 2017. Institutt for samfunnsmedisin - ISM skriftserie p. 17-20en_US
dc.identifier.cristinIDFRIDAID 1497819
dc.identifier.isbn978-82-8378-003-1
dc.identifier.urihttps://hdl.handle.net/10037/29129
dc.language.isoengen_US
dc.publisherUiT Norges arktiske universiteten_US
dc.relation.projectIDNorges forskningsråd: 270672en_US
dc.rights.accessRightsopenAccessen_US
dc.titleUsing machine learning to provide automatic image annotation for wildlife camera traps in the Arcticen_US
dc.type.versionsubmittedVersionen_US
dc.typeChapteren_US
dc.typeBokkapittelen_US


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