74558

Автор(ы): 

Автор(ов): 

4

Параметры публикации

Тип публикации: 

Глава в книге

Название: 

Detection and Characterization of Caviar Using a Neural Network Algorithm

ISBN/ISSN: 

978-981-99-4165-0

DOI: 

10.1007/978-981-99-4165-0_35

Наименование источника: 

  • Agriculture Digitalization and Organic Production

Город: 

  • St Petersburg, RUSSIA

Издательство: 

  • Springer

Год издания: 

2023

Страницы: 

383–395
Аннотация
Conservation and increase of fish resources is one of the priority tasks of modern society. Due to agricultural activities, the impact of the construction of hydroelectric power stations, as well as the widespread presence of poachers have led to the fact that fish resources need to be replenished in special fisheries. The article points out the importance and conservation of fish resources around the world, as well as the priority of caviar counting in the breeding of sturgeon species. Conducting such activities on the farms is necessary to monitor the impact and effectiveness of the use of various feeds, changing conditions, etc. Traditionally, two methods are used at enterprises to count caviar—by weight and volume, in addition, the von Bayer method with the use of a special tool is used in practice to count red caviar. The paper also considers high-performance digital methods of caviar counting, outstanding and requiring technical solutions to perform a design for automatic counting using neural network algorithms. An original design using a camera with Internet access is proposed. Results of experimental systems for sturgeon fish caviar reproduction are presented.

Библиографическая ссылка: 

Мещеряков Р.В., Русаков К.Д., Тевяшов Г.К., Мышкин А.В. Detection and Characterization of Caviar Using a Neural Network Algorithm / Agriculture Digitalization and Organic Production. St Petersburg, RUSSIA: Springer, 2023. С. 383–395.