Show simple item record

dc.contributor.advisorAnshus, Otto
dc.contributor.advisorBjørndalen, John Markus
dc.contributor.authorThomassen, Sigurd
dc.date.accessioned2018-01-22T12:26:27Z
dc.date.available2018-01-22T12:26:27Z
dc.date.issued2017-12-14
dc.description.abstractDue to the large increase of image data in animal surveillance, an effective and efficient way of labeling said data is required. Over the past few years the Climate-ecological Observatory for Arctic Tundra (COAT) project have deployed dozens of cameras in eastern Finnmark, Norway during winter, which have resulted in a large volume of wildlife images which is used to document the effects of climate change on animal ecosystems in the area. The images are manually labeled by biologists, and is a time-consuming task. This thesis presents the architecture, design and implementation of an image classification system to be used with the camera traps for in-situ analytics on accumulated image data for periodical updates. The system will automatically classify and label the images taken by the cameras. Using state-of-the-art Convolutional Neural Networks (CNNs) we train the system on previously labeled COAT image data. We train four different models based on the MobileNet architecture. The models vary in number of weights, and input image resolution. Results show that we can automatically classify images on a small computer like the Raspberry Pi, with an accuracy of 81.1% at 1.17 FPS, and a model size of 17Mb. In comparison a GPU computer achieves the same accuracy and model size, but it has a classification speed of 12.5 FPS.en_US
dc.identifier.urihttps://hdl.handle.net/10037/12000
dc.language.isoengen_US
dc.publisherUiT Norges arktiske universiteten_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2017 The Author(s)
dc.subject.courseIDINF-3981
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Kommunikasjon og distribuerte systemer: 423en_US
dc.subjectVDP::Mathematics and natural science: 400::Information and communication science: 420::Communication and distributed systems: 423en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Kunnskapsbaserte systemer: 425en_US
dc.subjectVDP::Mathematics and natural science: 400::Information and communication science: 420::Knowledge based systems: 425en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Systemutvikling og – arbeid: 426en_US
dc.subjectVDP::Mathematics and natural science: 400::Information and communication science: 420::System development and system design: 426en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Simulering, visualisering, signalbehandling, bildeanalyse: 429en_US
dc.subjectVDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation, visualization, signal processing, image processing: 429en_US
dc.titleEmbedded analytics of animal imagesen_US
dc.typeMaster thesisen_US
dc.typeMastergradsoppgaveen_US


File(s) in this item

Thumbnail
Thumbnail
Thumbnail

This item appears in the following collection(s)

Show simple item record