Özgün Bir Yaklaşim Ile Otomatik Gemi Tipi Siniflandirmasi

Umit Kacar, Deniz Kumlu, Murvet Kirci

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

2 Atıf (Scopus)

Özet

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.

Tercüme edilen katkı başlığıA Novel approach for automatic ship type classification
Orijinal dilTürkçe
Ana bilgisayar yayını başlığı2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 - Proceedings
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar2153-2156
Sayfa sayısı4
ISBN (Elektronik)9781467373869
DOI'lar
Yayın durumuYayınlandı - 19 Haz 2015
Etkinlik2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 - Malatya, Turkey
Süre: 16 May 201519 May 2015

Yayın serisi

Adı2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 - Proceedings

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???event.eventtypes.event.conference???2015 23rd Signal Processing and Communications Applications Conference, SIU 2015
Ülke/BölgeTurkey
ŞehirMalatya
Periyot16/05/1519/05/15

Bibliyografik not

Publisher Copyright:
© 2015 IEEE.

Keywords

  • Feature combining
  • Feature extraction
  • Object recognition
  • Ship type classification

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