title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐ¾ÑÑÐ¸ÑÐ¾Ð²ÐºÐ¸ ÑÐµÐ»ÑÑÐºÐ¾Ñ Ð¾Ð·ÑÐ¹ÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð¿ÑÐ¾Ð´ÑÐºÑÐ¸Ð¸ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐµÑ Ð½Ð¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð·ÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Development of an automatic system for sorting agricultural products based on the use of computer vision
Creators: name: ÐÑÐ±Ð¸Ð½Ð°, ÐÐ»ÐµÐ½Ð°
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: ÑÐµÐ»ÑÑÐºÐ¾Ñ Ð¾Ð·ÑÐ¹ÑÑÐ²ÐµÐ½Ð½Ð°Ñ Ð¿ÑÐ¾Ð´ÑÐºÑÐ¸Ñ
ÑÐ¾ÑÑÐ¸ÑÐ¾Ð²ÐºÐ°
ÑÐµÑ Ð½Ð¸ÑÐµÑÐºÐ¾Ðµ Ð·ÑÐµÐ½Ð¸Ðµ
Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð°Ñ ÑÐµÑÑ
ÐºÐ¾Ð½ÑÑÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð·
ÑÐ²ÐµÑÐ¾Ð²ÑÐµ ÑÐ¸Ð»ÑÑÑÑ
agricultural products
sorting
computer vision
neural network
contour analysis
color filters

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description: The purpose of this work is to develop an automated system for sorting agricultural products based on the use of computer vision to automate and speed up sorting processes. The object of the study is the sorting systems for agricultural products. The subject of the research is computer vision. Tasks performed during the work: â analysis of data on sorting methods; â analysis of existing sorting systems; â selection of the hardware of sorting system; â determination of the system operation design; â development and testing of an algorithm for obtaining products based on the use of classical methods of computer vision; â development and testing of an algorithm for obtaining products based on the use of neuron network. The work includes collecting data on methods and systems of agricultural productsâ sorting, selecting the hardware for the correct operation of the system. Also determining the structure of the work, creating a set of system data for training and testing the software part of the system. Finally developing the software part based on classical methods of computer vision, training and selection of an acceptable neural network model.