Abstract
Traditionally, the assessment of plants for different diseases is carried out by visual determination of leaf damage with the help of an expert – phytopathologist. This method has a number of disadvantages that are proposed to be overcome with the use of the automated system-cognitive analysis (ASC-analysis) of the spectra of images plants in the intelligent system called “Eidos”. For this purpose, we solve the following tasks: Task 1: formulating the idea and concept of the solution of the problem; Task 2: justifying the choice of the method and the tool to solve problems; Task 3: applying the selected method and the tool to solve the problems, i.e. to perform the following steps: – cognitive structuring of the subject area; – formalization of the subject area; – synthesis and verification of models; – improving the quality of the model and the choice of the most reliable models – solution in the most reliable model of diagnostic tasks (classification, recognition, identification), decision support and research of the modeled subject area by studying its model. Task 4: describing the effectiveness of the proposed solution. Task 5: examining the limitations and disadvantages of the proposed solutions for the problems and prospects of its development by overcoming those limitations and drawbacks. We also provide a detailed numerical example intellectual analysis of spectral images of plants with real data by applying the ASC-analysis and “Eidos” intellectual system. However, students and scientists still do not notice that open, scalable, interactive, intelligent online environment for learning and researches already exists and operates, based on automated systemcognitive analysis (ASC-analysis) and its programmatic Toolkit – intellectual “Eidos” and the author’s website. This article is an original presentation and it is designed to familiarize potential users with the capabilities of this environment.
Highlights
The idea of solving problems is to use modern technologies for this, which did not exist during the development of the traditional approach. These technologies are increasingly used in various fields of agriculture, such as precision agriculture, survey of agricultural lands on the basis of multispectral image acquisition and analysis; drones are used in environmental monitoring, in the assessment of dynamics of exogenous geological processes, in the inventory of objects of forestry, in the evaluation of the volumes of deforestation, in monitoring of agricultural land, etc
The spectra of source images are formed at formalization of the subject area, because they represent one of the stages of the process of formalization
They are presented (Figure 1), because it is easier to compare them with generalized spectra of the classes, which are formed at the synthesis stage of the model, and which will be considered
Summary
The degree of damage of plants by various diseases can be estimated using visual determination with the help of an expert in Phytopathology [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20] This method is characterized by a number of disadvantages: 1. The aim of this work is to develop a method and instrumentation that provides quantitative rapid assessment of the degree of destruction of plants in the conditions of the field using their images
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