IMAGE RECOGNITION OF AGRICULTURAL CROPS, PLANTS AND FORESTS

Abstract

The paper provides an overview of some studies on the recognition of images of crops, plants and forests. These image recognition systems use various methods of pre-processing, computer vision, and deep learning. Recently recognition systems based on mobile devices are increasing, which increases their availability and wide distribution. The articles on recognition, classification of fruits and fruits in orchards, the creation of a data bank of these agricultural products (apples, pears, kiwi) to assess ripening and yield are considered. The works devoted to the automation of harvesting grain crops are described on the example of the work of a combine harvester using machine vision. Crop production plays an important role in providing feed for animal husbandry; articles on the recognition of agricultural plants based on leaf images are analyzed. Also, by the condition of the leaves of potato bushes, you can determine their disease, assess the condition of the soil. The work on the development of mobile systems for monitoring and recognition of the process of growing mushrooms based on the "green house" technology for farms is presented. Using remote diagnostics, you can analyze and monitor the state of the surface of land and seas. For remote environmental monitoring of the landscape of the earth's surface, work is described on the recognition, classification of forests, water resources using hyperspectral analysis of satellite images.