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Ship detection from optical satellite images with deep learning

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

18 Atıf (Scopus)

Özet

The effective use and control of maritime routes in the commercial/military area is an increasing and important need for states. There are some motivations for this purpose: Safe traffic of the ships in narrow canals, avoiding illegal usage of anchoring areas of ships, monitoring fishing activities to avoid illegal fishing or protect fish population, detection of lost ships, boats or debris in the ocean, detection and identification of warships (intelligence, defense, offensive, etc.). This paper proposed an open source, fast running ship detection system from optical satellite images with the deep learning algorithm. The system does not need any comprehensive hardware, even can work on an average laptop. Tensorflow Object Detection Application Programming Interface (API)is trained by optical satellite images with ships and used as object detection API.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıProceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019
EditörlerS. Menekay, O. Cetin, O. Alparslan
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar479-484
Sayfa sayısı6
ISBN (Elektronik)9781538694480
DOI'lar
Yayın durumuYayınlandı - Haz 2019
Etkinlik9th International Conference on Recent Advances in Space Technologies, RAST 2019 - Istanbul, Turkey
Süre: 11 Haz 201914 Haz 2019

Yayın serisi

AdıProceedings of 9th International Conference on Recent Advances in Space Technologies, RAST 2019

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???event.eventtypes.event.conference???9th International Conference on Recent Advances in Space Technologies, RAST 2019
Ülke/BölgeTurkey
ŞehirIstanbul
Periyot11/06/1914/06/19

Bibliyografik not

Publisher Copyright:
© 2019 IEEE.

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