One Stage Deep Learning Based Method for Agricultural Parcel Boundary Delineation in Satellite Images


Awad B., Erer I.

13th International Conference on Electrical and Electronics Engineering, ELECO 2021, Virtual, Bursa, Türkiye, 25 - 27 Kasım 2021, ss.609-612 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.23919/eleco54474.2021.9677859
  • Basıldığı Şehir: Virtual, Bursa
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.609-612
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

© 2021 Chamber of Turkish Electrical Engineers.Boundary delineation is a rapidly evolving, significant research issue. It can be defined as identifying individual agricultural parcels and accurately outline their borders. Boundary delineation plays an important role in various application related to smart agriculture and precision farming. In this paper, a one stage deep learning method is utilized for boundary delineation. This is done by performing transfer learning and fine tuning the network using thousands of parcels. Later, the result of this network is compared to state-of-the-art models using spatially/temporally different dataset. The results are later discussed using common metrics.