Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification

Katarzyna Bobkowska; Izabela Bodus-olkowska Izabela

doi:10.2478/pomr-2020-0077

Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification

Abstrakt

This article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and Identification (SHREC) project. The image repository for the training purposes consists about 6,000 images of different categories of the vessels. Some images were gathered from internet websites, and some were collected by the project’s video cameras. The GoogLeNet network was trained and tested using 11 variants. These variants assumed modifications of image sets representing (e.g., change in the number of classes, change of class types, initial reconstruction of images, removal of images of insufficient quality). The final result of the classification quality was 83.6%. The newly obtained neural network can be an extension and a component of a comprehensive geoinformatics system for vessel recognition.

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Katarzyna Bobkowska dr inż.
Izabela Bodus-olkowska Izabela

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Wersja publikacji: Accepted albo Published Version
Licencja: otwiera się w nowej karcie

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Informacje szczegółowe

Kategoria:: Publikacja w czasopiśmie
Typ:: artykuły w czasopismach
Opublikowano w:: Polish Maritime Research nr 27, strony 170 - 178,
ISSN: 1233-2585
Język:: angielski
Rok wydania:: 2020
Opis bibliograficzny:: Bobkowska K., Bodus-Olkowska Izabela I.: Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification// Polish Maritime Research -Vol. 27,iss. 4(108) (2020), s.170-178
DOI:: Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.2478/pomr-2020-0077
Weryfikacja:: Politechnika Gdańska