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Annotation
В данной работе описаны основные понятия и методы распознавания образов. Изучены основные виды искусственных нейронных сетей для задач распознавания цифровых образов, проведен анализ. Рассмотрен фреймворк Hadoop его файловая система HDFS, потока данных MapReduce и библиотека deeplearning4j. Спроектирована приложение для распознавания образов с помощью фреймворка Hadoop и наборов данных MNIST. Разработаны классы для приложения с работой в параллельном режиме. Приложение протестировано на данных из интернета.
In the given work the basic concepts and methods of image recognition are described. The main types of artificial neural networks for the tasks of recognizing images are studied, the analysis is carried out. The Hadoop framework, its file system HDFS, analysis of the MapReduce data flow and the library Deeplearning4j are investigated. An application for image recognition was designed using the Hadoop framework and datasets. Classes have been developed for the application working in parallel mode. The application has been tested on random images from the Internet.
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