Ship recognition and classification using silhouettes extracted from optical images

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dc.citation.epage1620en_US
dc.citation.spage1617en_US
dc.contributor.authorYüksel, Göktuğ Kağanen_US
dc.contributor.authorYalıtuna, Buğraen_US
dc.contributor.authorTartar, Ömer Faruken_US
dc.contributor.authorAdlı, Faiz Caneren_US
dc.contributor.authorEker, Kaanen_US
dc.contributor.authorYörük, Onuren_US
dc.coverage.spatialZonguldak, Turkey
dc.date.accessioned2018-04-12T11:48:22Z
dc.date.available2018-04-12T11:48:22Z
dc.date.issued2016en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 16-19 May 2016en_US
dc.descriptionConference Name: IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016en_US
dc.description.abstractIn this paper, extraction of ship signatures from silhouette images of three-dimensional ship models and ship recognition from optical images are investigated. First of all, from the silhouette images of 3-dimensional ship models, with the help of feature vectors, ship signatures are created. Using three-dimensional ship models gets rid of the difficulty of obtaining real videos for the database and makes it possible to obtain information about ships from every angle. Then, created ship signatures are collected in a synthetic database. In the next stage, using segmentation and Artificial Neural Networks, ship recognition and classification are performed. In this paper, how all of the stages are done is explained and obtained numerical results are provided to illustrate used theoretical solutions.en_US
dc.description.provenanceMade available in DSpace on 2018-04-12T11:48:22Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2016en
dc.identifier.doi10.1109/SIU.2016.7496065en_US
dc.identifier.urihttp://hdl.handle.net/11693/37698
dc.language.isoTurkishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2016.7496065en_US
dc.source.titleProceedings of the IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016en_US
dc.subjectArtificial Neural Networksen_US
dc.subjectShip detectionen_US
dc.subjectShip recoginitionen_US
dc.titleShip recognition and classification using silhouettes extracted from optical imagesen_US
dc.title.alternativeOptik görüntülerden çıkarılan silüetler sayesinde gemi tanıması ve sınıflandırmasıen_US
dc.typeConference Paperen_US

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