{"title":"神经网络在低质量卫星图像分类中的应用","authors":"R. Malakhanov, V. Chizhov","doi":"10.31799/978-5-8088-1554-4-2021-2-44-47","DOIUrl":null,"url":null,"abstract":"The article offers a solution to the problem of classification of low-quality images of aircraft using convolutional neural networks. To solve this problem with sufficient accuracy, an analysis of popular architectural neural networks was performed, and the process of preparing the selected algorithm at all stages was described: preprocessing test data, training the neural network, and processing the results obtained.","PeriodicalId":318959,"journal":{"name":"The Second International Scientific Conference. Collection of reports","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"APPLICATION OF NEURAL NETWORKS IN CLASSIFICATION OF LOW-QUALITY SATELLITE IMAGERY\",\"authors\":\"R. Malakhanov, V. Chizhov\",\"doi\":\"10.31799/978-5-8088-1554-4-2021-2-44-47\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article offers a solution to the problem of classification of low-quality images of aircraft using convolutional neural networks. To solve this problem with sufficient accuracy, an analysis of popular architectural neural networks was performed, and the process of preparing the selected algorithm at all stages was described: preprocessing test data, training the neural network, and processing the results obtained.\",\"PeriodicalId\":318959,\"journal\":{\"name\":\"The Second International Scientific Conference. Collection of reports\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Second International Scientific Conference. Collection of reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31799/978-5-8088-1554-4-2021-2-44-47\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Second International Scientific Conference. Collection of reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31799/978-5-8088-1554-4-2021-2-44-47","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
APPLICATION OF NEURAL NETWORKS IN CLASSIFICATION OF LOW-QUALITY SATELLITE IMAGERY
The article offers a solution to the problem of classification of low-quality images of aircraft using convolutional neural networks. To solve this problem with sufficient accuracy, an analysis of popular architectural neural networks was performed, and the process of preparing the selected algorithm at all stages was described: preprocessing test data, training the neural network, and processing the results obtained.
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