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Plant Counting By Using k-NN Classification on UAVs Images

Date

2015

Author

Tavus, Mustafa Resit
Eker, Muhammed Emin
Senyer, Nurettin
Karabulut, Bunyamin

Metadata

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Abstract

In this study, Plant Counting was implemented by appling k-NN classification to images obtained from Unnamed Air Vehicle (UAV). Firstly, The images were subjected to erosion process by transforming different colour levels. The objects in the images were classified as plant and soil by means of k-NN classification. It was observed that plants can be counted with 87,7% of accuracy and 86,6% of precision by being performed last processing of the morphology of the binary image.

Source

2015 23Rd Signal Processing and Communications Applications Conference (Siu)

URI

https://hdl.handle.net/20.500.12712/14570

Collections

  • Scopus İndeksli Yayınlar Koleksiyonu [14046]
  • WoS İndeksli Yayınlar Koleksiyonu [12971]



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