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Abstract

This article analyzes the problems of implementing image recognition methods and algorithms for identifying biological objects. The Orthoptera group was chosen as a biological object. Orthoptera is a taxonomic order of insects that includes grasshoppers, crickets, locusts, and others. Approaches to the formation and identification of features of Orthoptera species and the formation of training and control samples of their samples are proposed. Estimation algorithms (ACE) were chosen as algorithmic support for identifying Orthoptera collections. ACE is based on the principle of partial priority. Approaches to the formation of a training and testing complex based on the data from the Orthoptera collections are proposed. The paper presents the process of developing an information-recognition system designed to solve problems related to the identification of Orthoptera, as well as experimental studies of the patterns of the grasshopper subfamily.

First Page

62

Last Page

66

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