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 başlığı | A Novel approach for automatic ship type classification |
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Orijinal dil | Türkçe |
Ana bilgisayar yayını başlığı | 2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 - Proceedings |
Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
Sayfalar | 2153-2156 |
Sayfa sayısı | 4 |
ISBN (Elektronik) | 9781467373869 |
DOI'lar | |
Yayın durumu | Yayınlandı - 19 Haz 2015 |
Etkinlik | 2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 - Malatya, Turkey Süre: 16 May 2015 → 19 May 2015 |
Yayın serisi
Adı | 2015 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 |
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Ülke/Bölge | Turkey |
Şehir | Malatya |
Periyot | 16/05/15 → 19/05/15 |
Bibliyografik not
Publisher Copyright:© 2015 IEEE.
Keywords
- Feature combining
- Feature extraction
- Object recognition
- Ship type classification