title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ ÑÑÐ°ÑÐ¸ÑÑÐ¸ÑÐµÑÐºÐ¸Ñ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² Ð´Ð»Ñ ÑÐ»ÑÑÑÐµÐ½Ð¸Ñ Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ 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° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Application of machine learning methods and statistical parameters to improve radar image segmentation performance
Creators: name: Ð Ð¾Ð¶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: Ð ÐÐ
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U-Net
DeeplabV3
radar image
segmentation
statistics
machine learning
deep learning
support vector machine
nearest neighbor method
naive bayes classifier

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description: The object of research is a method of segmentation of radar images using machine learning and statistics. The aim is to develop a method for segmentation of radar images using machine learning and statistical features to improve performance of the segmentation process. In the process of the work, the analysis of existing solutions and the development of our own method were carried out. In addition, a data set was created, the architecture of the proposed method was developed, its comparison with classical machine learning methods such as the support vector machine method, the nearest neighbor method, the naive Bayes classifier and with deep methods: U-Net and DeepLabV3. The results obtained show the effectiveness of the proposed approach in detecting water and land in the image. A high quality of segmentation and a level of performance exceeding known methods with minimal use of computing resources are achieved. This method is implemented using machine learning algorithms on a central processor. Given the limitations in aircraft and underwater vehicles, satellite systems in terms of weight, size and energy characteristics, it can be integrated into them.