Anatoliy M. Korovkin (anatoliy.korovkin@gmail.com)

Novosibirsk State University

Monitoring of ixodidae helps to detect changes in the ecological situation in the region under investigation and predict possible waves of transport of pathogenic viruses and microorganisms. In such statistics, the Ministry of Health, Sanitary-Epidemiological Station, and other public and private services are in need at the moment. The situation is complicated by the need for highly qualified specialists and the difficulty in determining by directories. To solve existing problems, software tools are needed to simplify the identification of ixodidae ticks.
The purpose of this research is the development of an expert system for the identification of ixodid ticks from photographs using neural networks. As a result, neural networks such as AlexNet and VGG were used. Acceptable results were obtained for use by specialists in real objectives. To provide client access to the server part, a public RESTful API is created

arthropods, ixodidae, machine learning, neural networks, classification