dc.contributor.advisor | Bjørndalen, John Markus | |
dc.contributor.author | Mathiassen, Truls | |
dc.date.accessioned | 2021-02-04T11:47:17Z | |
dc.date.available | 2021-02-04T11:47:17Z | |
dc.date.issued | 2020-11-10 | en |
dc.description.abstract | While monitoring rodents in the Arctic Tundra to evaluate if climate changes
affect the ecosystem. The camera-traps of the coat project generates image
data in large scale each year. To manually examine the data in regards to label-
ing is a tedious and time-consuming job, and a more efficient and automated
tool for the task is required.
In this thesis we presents the architecture, design and implementation of a
object classification model deployed on a small embedded computer, to be used
on the gathered image data in order to classify and label the animals at the
edge.
We conduct transfer-learning on the state-of-the-art pre-trained YOLOv4-tiny
model by introducing a labeled COAT image set. We utilize the Convolutional
Neural Network of the model to do predictions on a test image set in order to
evaluate the model. The result is an application with an embedded model able
to predict labels with an accuracy of 96.07% and inference time that classifies
it to do so in real-time. | en_US |
dc.identifier.uri | https://hdl.handle.net/10037/20516 | |
dc.language.iso | eng | en_US |
dc.publisher | UiT Norges arktiske universitet | no |
dc.publisher | UiT The Arctic University of Norway | en |
dc.rights.holder | Copyright 2020 The Author(s) | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/4.0 | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) | en_US |
dc.subject.courseID | INF-3981 | |
dc.subject | VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550::Datateknologi: 551 | en_US |
dc.subject | VDP::Technology: 500::Information and communication technology: 550::Computer technology: 551 | en_US |
dc.subject | VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550::Annen informasjonsteknologi: 559 | en_US |
dc.subject | VDP::Technology: 500::Information and communication technology: 550::Other information technology: 559 | en_US |
dc.title | Object detection at the edge | en_US |
dc.type | Mastergradsoppgave | nor |
dc.type | Master thesis | eng |