| Issue |
E3S Web Conf.
Volume 270, 2021
International scientific forum on computer and energy Sciences (WFCES 2021)
|
|
|---|---|---|
| Article Number | 01021 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/e3sconf/202127001021 | |
| Published online | 09 June 2021 | |
Neural network for identifying apple fruits on the crown of a tree
1
Federal Scientific Agroengineering Center VIM, 1-st Institutsky proezd, 5, Moscow, 109428, Russia
2
National University of Life and Environmental Sciences of Ukraine, Heroev Oborony str., 15, Kyiv, 03041, Ukraine
3
Taras Shevchenko National University of Kyiv, Volodymyrs’ka str., 64/13, Kyiv, 01601, Ukraine
* Corresponding author: alexeykutyrev@gmail.com
To identify the fruits on the crowns of trees and count their number, a software and hardware complex (PAC) based on a technical vision system and a recurrent neural network of deep learning has been developed. The created neural network and class allocation algorithms allow the software and hardware complex to function stably in the conditions of industrial horticultural plantings, regardless of the size and interference of foliage, to determine the color of the fruit surface, to identify the presence of diseases and defects of fruits. The developed package provides digital monitoring of both photographic materials and video streams in online mode.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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