dc.contributor.author | Rodin, Christopher D | |
dc.contributor.author | de Lima, L. N. | |
dc.contributor.author | Andrade, Fabio | |
dc.contributor.author | Haddad, D. B. | |
dc.contributor.author | Johansen, Tor Arne | |
dc.contributor.author | Storvold, Rune | |
dc.date.accessioned | 2019-01-07T11:56:04Z | |
dc.date.available | 2019-01-07T11:56:04Z | |
dc.date.created | 2018-12-26T21:40:36Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 2161-4393 | |
dc.identifier.uri | http://hdl.handle.net/11250/2579466 | |
dc.description.abstract | In recent years, the use of Unmanned Aerial Systems (UAS) has become commonplace in a wide variety of tasks due to their relatively low cost and ease of operation. In this paper, we explore the use of UAS in maritime Search And Rescue (SAR) missions by using experimental data to detect and classify objects at the sea surface. The objects are chosen as common objects present in maritime SAR missions: a boat, a pallet, a human, and a buoy. The data consists of thermal images and a Gaussian Mixture Model (GMM) is used to discriminate foreground objects from the background. Then, bounding boxes containing the object are defined and used to train a Convolutional Neural Network (CNN). The CNN achieves the average accuracy of 92.5% when evaluating a testing dataset. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | nb_NO |
dc.title | Object Classification in Thermal Images using Convolutional Neural Networks for Search and Rescue Missions with Unmanned Aerial Systems | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.journal | Proceedings of ... International Joint Conference on Neural Networks | nb_NO |
dc.identifier.doi | 10.1109/IJCNN.2018.8489465 | |
dc.identifier.cristin | 1647262 | |
dc.relation.project | Norges forskningsråd: 223254 | nb_NO |
dc.relation.project | EC/H2020/642153 | nb_NO |
dc.description.localcode | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | nb_NO |
cristin.unitcode | 194,63,25,0 | |
cristin.unitname | Institutt for teknisk kybernetikk | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |