A method of yield monitoring based on neural networks using deep learning

Abstract

Estimation of crop area is an important task in agriculture and can be used to provide accurate information on many issues such as crop yield estimation, food policy development, adjustment of planting patterns, which is of great importance for national food security. This article discusses yield monitoring based on the image segmentation method based on the work of neural networks using deep learning. For this purpose, a neural network based on the U-net architecture was selected and trained, and an algorithm was created for subsequent analysis of processed images.

Keywords

• semantic segmentation of images
• u-net
• object classification
• yield monitoring