title: Ð Ð°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ Ð¸ Ð¿Ð¾Ð´ÑÑÑÑ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð° ÑÑÐ»ÐµÐ½ÐµÐ¹ Ð¿Ð¾ ÑÐ½Ð¸Ð¼ÐºÐ°Ð¼ Ñ Ð±ÐµÑÐ¿Ð¸Ð»Ð¾ÑÐ½Ð¸ÐºÐ¾Ð²
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: Recognition and calculation of the number of seals from images from drones
Creators: name: ÐÐ°Ð½ÑÐºÐ¾Ð², ÐÐ¸ÐºÐ¸ÑÐ°
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: 2020
Subjects: ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ðµ Ð·ÑÐµÐ½Ð¸Ðµ
Ð·Ð°Ð´Ð°ÑÐ° Ñ ÑÐµÐ¼Ð°Ð½ÑÐ¸ÑÐµÑÐºÐ¸Ð¼ ÑÐ°Ð·ÑÑÐ²Ð¾Ð¼
computer vision
semantic break task

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description: The subject of the graduate qualification work is Â«Recognition and calculation of the number of seals from images from dronesÂ». In this paper, I study the techniques and methods of computer vision and machine learning, used in recognition and classification of objects in photographs. The purpose of the work was building an algorithm that effectively solves the problem of detecting and recognizing seals in pictures from drones, according to established criteria of efficiency. The work itself includes formalization of the task, the decomposition of the task into separate stages, and software implementation of all stages with the python programming language, followed by analysis of the effectiveness of the created software solution. It is worth noting that the created solution is a combination of computer vision methods for detecting objects and classification of found objects using a neural network. The result algorithm is fully satisfies the set quality criteria. Software implementation allows you to automate the process of manual analysis of large image flow, and also receive various metrics for a specific selection of photos. My program is already being put into practice by real users, which talks about the importance and relevance of the obtained solution in real life and in real problems. Based on the results of the work, we can see the effectiveness of the joint application of classical techniques computer vision and machine learning, which together allows you to build flexible solutions for the most different applied problems that cannot be solved using only one of the approach.