This work classifies the ship types from color images by using cameras mounted on ships. Our data set contains 10 different ship types. The synthetic images used for training imported from Google 3D Warehouse. Test data set imported from Google Images and contains real ship images. This work aims to classify real ship images by using synthetic images. We present a novel approach for combining four features extracted from synthetic images and we have achieved % 90 accuracy.


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    Title :

    A Novel approach for automatic ship type classification


    Contributors:
    Kacar, Umit (author) / Kumlu, Deniz (author) / Kirci, Murvet (author)


    Publication date :

    2015-05-01


    Size :

    417909 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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