Abstract:

Nowadays, many different tools can be used to classify images, each of which is aimed at solving a certain range of tasks. This article provides a brief overview of libraries and technologies for image classification. The architecture of a simple convolutional neural network for image classification is built. Image recognition experiments have been conducted with popular neural networks such as VGG 16 and ResNet 50. Both neural networks have shown good results. However, ResNet 50 overfitted due to the fact that the dataset contained the same type of images for training, since this neural network has more layers that allow reading the attributes of objects in the images. A comparative analysis of image recognition specially prepared for this experiment was carried out with the trained models.

Abstract:

Relevance of the issue under study is due to tenuity of methods proposed by other researchers that use simple heuristics or machine learning algorithms. The purpose of the article is to provide better way to extract titles from scientific PDF documents and offer better and more reasonable approach to title selection generally. The leading approach to the study is regard as many cases and problems appeared during extraction as possible and find an approach to solve all of them. The results showed the efficiency of chosen approach in case of having a document set with all of considered problems. The research highlights that deep analysis of current task problem is a perspective to make the best solutions and tools. The article may be useful for all researchers and developers who often encounter the problem of document structural analysis or title detection as secondary task of a main program workflow.

Abstract: The spatial data portal GeoMeta is described as a standardized and decentralized spatial information management environment, designed for access to geodata, cartographic products and related metadata from various sources. The main features of the portal are discussed, with the accent on the expansions, realized in its last versions.

Abstract: Подводятся итоги работы по созданию Электронного архива академика А. П. Ершова, рассказывается о некоторых интересных страницах этого архива, о технологических особенностях проектных решений, о деталях реализации проекта.