Intellectual analysis of spectral images of plants

Abstract

Traditionally, the assessment of plants for different diseases is carried out by visual determination of leaf damage with the help of an expertphytopathologist. 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 modelssolution 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.