title: ÐÐµÑÐ¾Ð´Ð¸ÐºÐ° ÑÑÑÐ½Ð¾Ð¹ ÑÐ°Ð·Ð¼ÐµÑÐºÐ¸ ÑÐ¿ÑÑÐ½Ð¸ÐºÐ¾Ð²ÑÑ ÑÐ½Ð¸Ð¼ÐºÐ¾Ð² Ð·ÐµÐ¼Ð½Ð¾Ð¹ Ð¿Ð¾Ð²ÐµÑÑ Ð½Ð¾ÑÑÐ¸ Ñ ÐºÐ¾ÑÐ¼Ð¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð°Ð¿Ð¿Ð°ÑÐ°ÑÐ° ÐÐ¸ÑÑ-2Ð
title: The technique of manual marking of satellite images of the earthâs surface from the Aist-2D spacecraft
Creators: name: ÐÐ¾Ð´Ð¼Ð°ÑÑÐºÐ¾Ð²Ð°, ÐÐ¸ÐºÑÐ¾ÑÐ¸Ñ
name: ÐÐµÑÑÑÐµÐ²Ð°, ÐÐ»ÐµÐºÑÐ°Ð½Ð´ÑÐ°
name: "Ð¡Ð¸ÑÑÐµÐ¼Ð½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð² Ð¿ÑÐ¾ÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ð¸ Ð¸ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ð¸", Ð¼ÐµÐ¶Ð´ÑÐ½Ð°ÑÐ¾Ð´Ð½Ð°Ñ Ð½Ð°ÑÑÐ½Ð¾-Ð¿ÑÐ°ÐºÑÐ¸ÑÐµÑÐºÐ°Ñ ÐºÐ¾Ð½ÑÐµÑÐµÐ½ÑÐ¸Ñ (26; 2022; Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³)
Publisher: name: ÐÐÐÐÐ¢ÐÐ¥-ÐÐ ÐÐ¡Ð¡
Year: 2023
Subjects: ÐÐ±ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
ÑÐ°Ð·Ð¼ÐµÑÐºÐ°
ÑÐºÐ¾Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¸Ð¹ Ð¼Ð¾Ð½Ð¸ÑÐ¾ÑÐ¸Ð½Ð³
ÐºÐ¾ÑÐ¼Ð¸ÑÐµÑÐºÐ¸Ðµ ÑÐ½Ð¸Ð¼ÐºÐ¸
Ð´Ð°ÑÐ°ÑÐµÑ
markup
environmental monitoring
satellite images
dataset

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description: The aim of the work is to develop a methodology for marking images of the Earthâs surface obtained from the Aist-2D spacecraft. In this work, the algorithms of classical manual image segmentation proposed by the authors of the article are applied, as well as training and test images are manually marked up for subsequent analysis and application in the field of deep convolutional neural networks in the class âwater spaceâ, which includes such objects as âriversâ and âreservoirsâ. To do this, a multifunctional Adobe Photoshop graphic editor was used, which has various tools for quickly selecting objects, such as âMagic Wandâ, âObject Selectionâ and âQuick Selectionâ. The study confirmed the quality and accuracy of the found segments, and also underwent subsequent processing during the training of a deep convolutional neural network.