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

Abstract

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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Category:: Articles
Type:: artykuły w czasopismach
Published in:: Polish Maritime Research no. 27, pages 170 - 178,
ISSN: 1233-2585
Language:: English
Publication year:: 2020
Bibliographic description:: 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:: Digital Object Identifier (open in new tab) 10.2478/pomr-2020-0077
Verified by:: Gdańsk University of Technology