title: Ð Ð°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð½Ð° Ð¼Ð¾ÑÑÐºÐ¾Ð¹ Ð¿Ð¾Ð²ÐµÑÑ Ð½Ð¾ÑÑÐ¸ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð³Ð»ÑÐ±Ð¾ÐºÐ¸Ñ Ð¿ÑÐµÐ´Ð¾Ð±ÑÑÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹
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 of objects on the sea surface using deep pre-trained neural networks
Creators: name: ÐÐ¸ÑÐ°ÑÐ¸Ð½Ð°, Ð¢Ð°ÑÑÑÐ½Ð°
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: 2022
Subjects: ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ Ð¾Ð±ÑÐµÐºÑÐ¾Ð²
Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÑÑÐ°Ð½ÑÑÐµÑÐ½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
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object recognition
neural networks
transfer learning
efficiency of input data preparation

description: Ð¢ÐµÐ¼Ð° Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ: Â«Ð Ð°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð½Ð° Ð¼Ð¾ÑÑÐºÐ¾Ð¹ Ð¿Ð¾Ð²ÐµÑÑÐ½Ð¾ÑÑÐ¸ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð³Ð»ÑÐ±Ð¾ÐºÐ¸Ñ Ð¿ÑÐµÐ´Ð¾Ð±ÑÑÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹Â». ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° Ð°Ð´Ð°Ð¿ÑÐ°ÑÐ¸Ð¸ Ð³Ð»ÑÐ±Ð¾ÐºÐ¸Ñ Ð¿ÑÐµÐ´Ð¾Ð±ÑÑÐµÐ½Ð½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð´Ð»Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð½Ð° Ð¼Ð¾ÑÑÐºÐ¾Ð¹ Ð¿Ð¾Ð²ÐµÑÑÐ½Ð¾ÑÑÐ¸. ÐÐ°Ð´Ð°ÑÐ¸, ÐºÐ¾ÑÐ¾ÑÑÐµ ÑÐµÑÐ°Ð»Ð¸ÑÑ Ð² ÑÐ¾Ð´Ðµ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸: ÐÐ·ÑÑÐµÐ½Ð¸Ðµ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¾Ð±ÑÐµÐºÑÐ¾Ð²; Ð¡ÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ: SGDM, RMSProp, Adam;ÐÐ±ÑÑÐµÐ½Ð¸Ðµ, ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¸ÑÑÐ»ÐµÐ´ÑÐµÐ¼ÑÑ ÑÐµÑÐµÐ¹ Ð¸ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð²; ÐÐ¾Ð´Ð³Ð¾ÑÐ¾Ð²ÐºÐ° Ð½Ð¾Ð²Ð¾Ð³Ð¾ Ð½Ð°Ð±Ð¾ÑÐ° Ð²ÑÐ¾Ð´Ð½ÑÑ Ð´Ð°Ð½Ð½ÑÑ; ÐÐ±ÑÑÐµÐ½Ð¸Ðµ, ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¸ÑÑÐ»ÐµÐ´ÑÐµÐ¼ÑÑ ÑÐµÑÐµÐ¹ Ð½Ð° Ð½Ð¾Ð²Ð¾Ð¼ Ð½Ð°Ð±Ð¾ÑÐµ Ð´Ð°Ð½Ð½ÑÑ Ð¸ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð². Ð ÑÐ¾Ð´Ðµ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ» Ð¿ÑÐ¾Ð¸Ð·Ð²ÐµÐ´ÐµÐ½ Ð¾Ð±Ð·Ð¾Ñ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¾Ð±ÑÐµÐºÑÐ¾Ð². ÐÑÐ» Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ (SGDM, RMSProp, Adam) Ð³Ð»ÑÐ±Ð¾ÐºÐ¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸, Ð¸ Ð°Ð½Ð°Ð»Ð¸Ð· ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ 5 Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ (SqueezeNet, GoogLeNet, ResNet-50, EfficientNet-b0, DarkNet-53). Ð¢Ð°ÐºÐ¶Ðµ Ð±ÑÐ»Ð¾ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ðµ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ðµ Ð´Ð»Ñ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ Ð½Ð¾Ð²Ð¾Ð³Ð¾ Ð½Ð°Ð±Ð¾ÑÐ° Ð²ÑÐ¾Ð´Ð½ÑÑ Ð´Ð°Ð½Ð½ÑÑ, Ð¸ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² ÑÐ°Ð±Ð¾ÑÑ ÑÐµÑÐµÐ¹ Ð½Ð° Ð¿Ð¾Ð´Ð³Ð¾ÑÐ¾Ð²Ð»ÐµÐ½Ð½ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð¸ Ð½Ð° Ð¸ÑÑÐ¾Ð´Ð½ÑÑ. Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð²ÑÐµ Ð¸ÑÑÐ»ÐµÐ´ÑÐµÐ¼ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸ Ð±ÑÐ»Ð¸ Ð°Ð´Ð°Ð¿ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ñ Ð´Ð»Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð½Ð° Ð¼Ð¾ÑÑÐºÐ¾Ð¹ Ð¿Ð¾Ð²ÐµÑÑÐ½Ð¾ÑÑÐ¸.
description: The topic of the graduate qualification work is âRecognition of objects on the sea surface using deep pre-trained neural networksâ. This work is devoted to the adaptation of deep pre-trained neural networks for the recognition of objects on the sea surface. Tasks that were solved during the development:Study of existing object recognition methods;Comparison of training methods: SGDM, RMSProp, Adam;Training, testing of the studied networks and comparison of results;Preparing a new set of input data;Training, testing of the studied networks on a new data set and comparing the results.In the course of this work, an overview of existing object recognition methods was made. A comparative analysis of training methods (SGDM, RMSProp, Adam) of deep neural classification networks was carried out, and an analysis of the results of training and testing of 5 neural networks (SqueezeNet, GoogLeNet, ResNet-50, EfficientNet-b0, DarkNet-53). Software was also developed to create a new set of input data, and a comparative analysis of the results of the networks on the prepared data and on the source data was carried out.As a result, all the studied neural networks were adapted to recognize objects on the sea surface.