title: ÐÐ½Ð°Ð»Ð¸Ð· Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐµÐ¹ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ ÑÐ°Ð·ÑÐµÑÐµÐ½Ð¸Ñ ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
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: Analysis of the features of using deep learning methods to increase the resolution of radar images
Creators: name: ÐÐ°Ð·Ð¸ÑÐ¾Ð², ÐÐ°ÑÐ°Ñ
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: Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ðµ ÑÐ°Ð·ÑÐµÑÐµÐ½Ð¸Ñ
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ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ðµ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ðµ
resolution enhancment
neural network
generative-adversarial network
convolutional neural network
syntheic aperture
metric
radar imagery

description: ÐÐ±ÑÐµÐºÑÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ â ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½ÑÐµ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ ÑÐ¾ ÑÐ¿ÑÑÐ½Ð¸ÐºÐ¾Ð² Ñ ÑÐ¸Ð½ÑÐµÐ·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¹ Ð°Ð¿ÐµÑÑÑÑÐ¾Ð¹ Ð¸ Ð¼ÐµÑÐ¾Ð´Ñ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ ÑÐ°Ð·ÑÐµÑÐµÐ½Ð¸Ñ ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹. Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â Ð°Ð½Ð°Ð»Ð¸Ð· Ð¿ÑÐ¸Ð¼ÐµÐ½Ð¸Ð¼Ð¾ÑÑÐ¸ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²ÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð´Ð»Ñ ÑÐ²ÐµÐ»Ð¸ÑÐµÐ½Ð¸Ñ ÑÐ°Ð·ÑÐµÑÐµÐ½Ð¸Ñ ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ Ð¸ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ñ Ð´ÑÑÐ³Ð¸Ð¼Ð¸ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ð¼Ð¸ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð±ÑÐ»Ð° Ð´Ð°Ð½Ð° Ð¾ÑÐµÐ½ÐºÐ° ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ¹ Ð´Ð»Ñ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ ÑÐ°Ð·ÑÐµÑÐµÐ½Ð¸Ñ ÑÐ°Ð´Ð¸Ð¾Ð»Ð¾ÐºÐ°ÑÐ¸Ð¾Ð½Ð½ÑÑ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹. ÐÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²Ð¾Ð¹ Ð¼ÐµÑÐ¾Ð´ Ð±ÑÐ» ÑÑÐ°Ð²Ð½ÐµÐ½ Ñ Ð´ÑÑÐ³Ð¸Ð¼Ð¸ Ð½ÐµÐ»Ð¸Ð½ÐµÐ¹Ð½ÑÐ¼Ð¸ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ ÑÐ°Ð·ÑÐµÑÐµÐ½Ð¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹. Ð¡ÑÐµÐ´Ð¸ Ð¸ÑÑÐ»ÐµÐ´ÑÐµÐ¼ÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð±ÑÐ» Ð²ÑÐ±ÑÐ°Ð½ ÑÐ°Ð¼ÑÐ¹ ÑÑÑÐµÐºÑÐ¸Ð²Ð½ÑÐ¹. ÐÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐ¸ ÑÑÑÑÐºÑÑÑÑ ÑÐ°Ð¼Ð¾Ð³Ð¾ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾Ð³Ð¾ Ð¼ÐµÑÐ¾Ð´Ð° Ð¿Ð¾Ð´ÑÐ¾Ð±Ð½Ð¾ Ð¸Ð·ÑÑÐµÐ½Ñ. ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ Ð¾ÑÐºÑÑÑÑÐµ Ð¾Ð±ÑÐ°Ð·Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½ÑÐµ ÑÐµÑÑÑÑÑ Ð¸ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ñ Ð¿Ð¾Ð¸ÑÐºÐ° Ð¸ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¸. ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ ÑÑÐµÐ´ÑÑÐ²Ð° Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð°ÑÐ¸Ð¸ (Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¹) ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸, ÑÐ·ÑÐº Ð¸ Ð¸Ð½ÑÐµÑÐ¿ÑÐµÑÐ°ÑÐ¾Ñ Python.
description: The objects of study are radar images from synthetic aperture radar satellites and methods for increasing the resolution of radar images. The purpose of the work is to analyze the applicability of neural network methods for increasing the resolution of radar images and compare them with other existing methods. As a result of the study, the effectiveness of using neural networks to enhance the resolution of radar images was assessed. The neural network method was compared with other nonlinear methods for image enhancement. Among the methods studied, the most effective was chosen. The structural features of the most effective method have been studied in detail. Open educational resources and programs for searching and analyzing information were used. Automation tools development, Python language and interpreter were used.