Аннотации:
The use of deep learning algorithms for the classification of crop diseases is
one of the promising areas in agricultural technology. This is due to the need
for rapid and accurate detection of plant diseases, which allows timely
measures to be taken to treat them and prevent their spread. One of them is
to increase productivity and maintain land quality through the timely
detection of diseases and pests in agriculture and their elimination.
Traditional classification methods in machine learning and algorithms in
deep learning were compared to note the high accuracy in detecting pests
and crop diseases. The advantages and disadvantages of each model
considered during training were taken into account, and the Inception V3
algorithm was incorporated into the application. They can monitor the
condition of crops on a daily basis with the help of new technologyapplications on gadgets. Aerial photographs used by research institutes and
agricultural grain centers do not show the changes that occur in agricultural
grains, that is, diseases and pests. Therefore, the method proposed in this
paper determines the types of diseases and pests of cereals through a mobile
application and suggests ways to deal with them.
