Sea Turtle Detection Using Faster R-CNN for Conservation Purpose

Badawy M., DİREKOĞLU C.

10th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions (ICSCCW), Prague, Çek Cumhuriyeti, 27 - 28 Ağustos 2019, cilt.1095, ss.535-541, (Tam Metin Bildiri) identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 1095
  • Doi Numarası: 10.1007/978-3-030-35249-3_68
  • Basıldığı Şehir: Prague
  • Basıldığı Ülke: Çek Cumhuriyeti
  • Sayfa Sayıları: ss.535-541
  • Orta Doğu Teknik Üniversitesi Kuzey Kıbrıs Kampüsü Adresli: Evet

Özet

Automatically monitoring see turtles over extensive coastlines is an important task for environmental research and conservation nowadays. Unfortunately, some of the sea turtle species have become endangered today and this is why there is a need for search-and-rescue. Computer vision algorithms can be used for sea turtle detection and monitoring. Recently, due to the powerful Convolutional Neural Networks (CNNs), computer vision crucial applications came to reality. Although such algorithms are computationally expensive, they have proved promising results where real-time applications can be feasibly implemented given high-capability GPUs. In this paper, we present a system of sea turtles detection using a Faster R-CNN algorithm. This system performs the sea turtles' detection on a cloud (off-board). Our detection algorithm can be performed using a static camera, or a moving camera that is mounted on UAVs for surveillance, search-and-rescue purposes.