Naslov
Individual Olive Tree Detection in RGB Images

Autori
Marin, Ivana ; Gotovac, Sven ; Papić, Vladan

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
SoftCOM 2022: 30th International Conference on Software, Telecommunications and Computer Networks: Proceedings / Begušić, Dinko ; Rožić, Nikola ; Radić, Joško ; Šarić, Matko - Split : Fakultet elektrotehnike, strojarstva i brodogradnje Sveučilišta u Splitu, 2022, 1-6

ISBN
978-953-290-117-7

Skup
30th International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2022

Mjesto i datum
Split, Hrvatska, 22.09.2022. - 24.09.2022

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Tree crowns ; Tree detection ; Remote sensing ; Deep learning

Sažetak
In this paper, an automatic method for detecting and counting olive trees in RGB images acquired by an unmanned aerial vehicle (UAV) is developed. Our approach is based on implementation of RetinaNet model and DeepForest Phyton package. For improvement of pretrained model via transfer learning, five olive groves were mapped using UAV, trees were manually labeled, and new image dataset was created. Several models were built, each being trained and evaluated on different set of images from selected olive groves. Experimental results obtained on a UAV image acquired over test olive groves are reported and discussed. Detection results showed high reliability of proposed approach and great improvement in performance compared to pretrained model.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA