convolutional neural network

Information Support for Personalities Socialization Processes Based on Common Interests

The main objective of this article is to create an information system project for socialization by personal interests on the basis of SEO-technologies and methods of machine learning. The main purpose of this information system is to identify the user within the system using neural networks and to select similar users by analysing the user's current information. An information system was created that, through Identity and JWT tokens, provides optimized and secure authorization, logging, and support functions for the current system user session.

Methods for real-time object searching and recognizing in video images on ios mobile platform

The features of the most common methods and systems for searching and recognizing objects in video are explored. The research shows the feasibility of building search and recognition tools for the iOS platform in real time. The method of functional adaptation of the algorithm of search and recognition of objects to features of video is offered, which consists in processing of video image by smoothing and minimization filters, which reduces the time of search and recognition of objects. The block diagram and algorithm of system functioning were designed.

SYNTHESIS OF BIOMEDICAL IMAGES BASED ON GENERATIVE ADVERSARIAL NETWORKS

Mo­dern da­ta­ba­ses of bi­ome­di­cal ima­ges ha­ve be­en in­ves­ti­ga­ted. Bi­ome­di­cal ima­ging has be­en shown to be ex­pen­si­ve and ti­me con­su­ming. A da­ta­ba­se of ima­ges of pre­can­ce­ro­us and can­ce­ro­us bre­asts "BPCI2100" was de­ve­lo­ped. The da­ta­ba­se con­sists of 2,100 ima­ge fi­les and a MySQL da­ta­ba­se of me­di­cal re­se­arch in­for­ma­ti­on (pa­ti­ent in­for­ma­ti­on and ima­ge fe­atu­res). Ge­ne­ra­ti­ve ad­ver­sa­ri­al net­works (GAN) ha­ve be­en fo­und to be an ef­fec­ti­ve me­ans of ima­ge ge­ne­ra­ti­on.

Method of image symbol recognition on the basis of convolutional neural network

In this article, a system of handwritten or printed text recognition in the image has been developed. Empirical methods of image processing and statistical models of machine learning and simulation are being developed in two directions: the detection of text on the image and the recognition of the text. Thus, in this paper, algorithmic software tools that combine these two areas in the software created for the operating systemiOS 11.0 or later for devices of the company Apple – iPhone, iPad that support this operating system are developed.