  Over the past decade, unprecedented progress in the development of neural
networks influenced dozens of different industries, including weed recognition
in the agro-industrial sector. The use of neural networks in agro-industrial
activity in the task of recognizing cultivated crops is a new direction. The
absence of any standards significantly complicates the understanding of the
real situation of the use of the neural network in the agricultural sector. The
manuscript presents the complete analysis of researches over the past 10 years
on the use of neural networks for the classification and tracking of weeds due
to neural networks. In particular, the analysis of the results of using various
neural network algorithms for the task of classification and tracking was
presented. As a result, we presented the recommendation for the use of neural
networks in the tasks of recognizing a cultivated object and weeds. Using this
standard can significantly improve the quality of research on this topic and
simplify the analysis and understanding of any paper.
