{"title":"Text classification using convolutional neural network","authors":"L. E. Sapozhnikova, O. Gordeeva","doi":"10.18287/1613-0073-2019-2416-219-226","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-219-226","url":null,"abstract":"In this article, the method of text classification using a convolutional neural network is presented. The problem of text classification is formulated, the architecture and the parameters of a convolutional neural network for solving the problem are described, the steps of the solution and the results of classification are given. The convolutional network which was used was trained to classify the texts of the news messages of Internet information portals. The semantic preprocessing of the text and the translation of words into attribute vectors are generated using the open word2vec model. The analysis of the dependence of the classification quality on the parameters of the neural network is presented. The using of the network allowed obtaining a classification accuracy of about 84%. In the estimation of the accuracy of the classification, the texts were checked to belong to the group of semantically similar classes. This approach allowed analyzing news messages in cases where the text themes and the number of classification classes in the training and control samples do not equal.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91538455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal tuning of the contour analysis method to recognize aircraft on remote sensing imagery","authors":"E. Dremov, S. Miroshnichenko, V. Titov","doi":"10.18287/1613-0073-2019-2391-222-232","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-222-232","url":null,"abstract":"In this paper, we describe the experimental results of aircraft recognition on optical remote sensing imagery using the theory of contour analysis. We propose the a method to calculate optimal values of the contour’s items quantity and the classification threshold through measuring within- and between-class distances for all possible training set instances combinations with followed by detection and minimization of the type I and II errors. We discuss the construction of contours’ similarity measures combining the principles of finding the most appropriate reference instance and calculating the average value for the whole class. It is shown that the proposed parameters' tuning method and the similarity function make contour analysis capable to train on compact non-uniform datasets and to recognize aircraft on the noisy and less detailed images.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89591406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Development of the documents comparison module for an electronic document management system","authors":"M. Mikheev, P. Yakimov","doi":"10.18287/1613-0073-2019-2416-527-533","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-527-533","url":null,"abstract":"The article is devoted to solving the problem of document versions comparison in electronic document management systems. Systems-analogues were considered, the process of comparing text documents was studied. In order to recognize the text on the scanned image, the technology of optical character recognition and its implementation — Tesseract library were chosen. The Myers algorithm is applied to compare received texts. The software implementation of the text document comparison module was implemented using the solutions described above.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88901012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis of the preferences of public transport passengers in the task of building a personalized recommender system","authors":"A. Borodinov, V. Myasnikov","doi":"10.18287/1613-0073-2019-2391-198-205","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-198-205","url":null,"abstract":"The paper presents the theoretical and algorithmic aspects for making a personalized recommender system (mobile service) designed for public route transport users. The main focus is on identifying and formalizing the concept of \"user preferences\", which is the basis of modern personalized recommender systems. Informal (verbal) and formal (mathematical) formulations of the corresponding problems of determining \"user preferences\" in a specific spatial-temporal context are presented: the preferred stops definition and the preferred \"transport correspondence\" definition. The first task can be represented as a well-known classification problem. Thus, it can be formulated and solved using well-known pattern recognition and machine learning methods. The second is reduced to the construction of dynamic graphs series. The experiments were conducted on data from the mobile application \"Pribyvalka-63\". The application is the tosamara.ru service part, currently used to inform Samara residents about the public transport movement.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81634282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The peculiarities of interaction between the end-user and the remote sensing system for spatial objects detection and recognition","authors":"","doi":"10.18287/1613-0073-2019-2391-250-257","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-250-257","url":null,"abstract":"The paper discusses the requirements for the system of remote sensing (hereinafter referred to as “System”) which is focused on the end user (EU), based on the concepts of object-oriented monitoring. The classification of simple queries generated with interactive tools in the context of the end user’s subject area is presented. The research investigates the features of the System needed for maintaining task-setting interaction, such as the subject ontology, including knowledge about the object of interest, its static and dynamic properties, the hierarchy of vector layers that describe spatial objects, the updated image database. The authors indicate the resources necessary for solving specific tasks, including spatial data repository and specification of computational procedures capable of interpreting the query in terms of decision operators. Specifically, the paper considers the structure of task-setting interaction tools, which ensures the object space-time localization, finding its meaning in semantic space, performance specification parameters measured one time or in dynamics, requirements for the visualization of the results and the activity of the System in relation to the end user in the monitoring process. The solutions presented were tested on monitoring the condition of agricultural lands in the multi-task space monitoring system of the Institute of Space and Information Technology, Siberian Federal University, Krasnoyarsk.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87527169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Berkholts, A. I. Frid, Murat Guzairov, A. Kirillova
{"title":"Integrity control algorithms in the system for telemetry data collecting, storing and processings","authors":"V. Berkholts, A. I. Frid, Murat Guzairov, A. Kirillova","doi":"10.18287/1613-0073-2019-2416-487-503","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-487-503","url":null,"abstract":"The issues of improving the security of the modular system for collecting, storing and processing telemetric information on the state of the onboard subsystems of the aircraft in automatic mode are considered. It is based on an analysis of the use of modern technologies for the protection and processing of telemetric information to ensure certain aspects of the guaranteeability of the system as a whole.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88406632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An investigation of machine learning method based on fractal compression","authors":"E. Minaev","doi":"10.18287/1613-0073-2019-2416-204-208","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-204-208","url":null,"abstract":"In this article the method of machine learning with cyclic fractal coding and the use of domain block dictionary, adapted for use on mobile platforms, with optimization of performance and volume of stored fractal images is investigated. The main idea of the method is to use the fractal compression method based on iterated function systems to reduce the dimension of the original images, and to use cyclic fractal coding to represent the class of images. As a result of research of the method it was found that the share of correctly recognized objects on MSTAR averages 0.892, the recognition time averages 254 ms. The achieved results are acceptable for use in mobile platforms, including UAVs and ground autonomous robots.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"143 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78203972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identification of thawed and frozen soil state in some Siberia regions by multi-temporal Sentinel 1 radar data in 2017-2018","authors":"N. Rodionova","doi":"10.18287/1613-0073-2019-2416-1-10","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-1-10","url":null,"abstract":"The paper deals with the identification of thawed/frozen soils in the topsoil layer for three stations in Siberia: Salekhard, Tiksi and Norilsk by using Sentinel 1B C-band radar data for the period of 2017-2018. Determination of the frozen/thawed soil state is carried out in three ways: 1) by multi-temporal radar data on the basis of a significant in 3-5 dB difference in the backscatter coefficient 0 in the transition of freezing/thawing soil state, 2) by finding the threshold value of 0 at which the temperature in the topsoil layer falls below 00C, 3) by texture features. The first method allows determining the period of time during which the process of freezing/thawing of the soil occurs. The second and third methods allow making local maps of frozen/thawed soils. It is shown that for the studied areas the Spearman correlation coefficient between 0 and air temperature for cross - polarization exceeds the correlation coefficient for co-polarization. The graphs of the AFI (air freezing index) for the period of 2012-2018 are constructed based on the archive data of air temperature for the study areas.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"79 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76706426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Expert system of food sensory evaluation for mobile and tablet","authors":"M. Nikitina, Y. Ivashkin","doi":"10.18287/1613-0073-2019-2416-332-339","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-332-339","url":null,"abstract":"One of the main directions of statistics in sensory evaluation is an assessment of the dependence between experimental variables and measured characteristics. Statistical criteria are used to assess a degree of interaction between variables, a level of experimental effects, and allow accepting or rejecting hypothesis proposed. In sensory evaluation, people act as measurement instruments, and a variation associated with the human factor arises. This proves that the use of statistical methods is necessary. This article represents a network computer system for collection and evaluation of food sensory indicators based on the methods of rank correlation and multifactorial analysis of variance in real time. The article describes information technology of expert sensory evaluation of food quality by individual panelists and sensory panels regarding the indicators that are not measured by technical means of control, based on client-server network architecture. The software implementation of system for collecting and statistical processing of sensory data based on the principles of multifactorial analysis of variance in real-time mode makes it possible to evaluate the influence of the human factor on objectiveness and reliability of sensory evaluation results, as well as to visualize the data of expert scores by various expert panels.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"101 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77328879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of convolution neural networks in eye fundus image analysis","authors":"N. Ilyasova, A. Shirokanev, I. Klimov","doi":"10.18287/1613-0073-2019-2416-74-79","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-74-79","url":null,"abstract":"In this work, we proposed a new approach to analyzing eye fundus images that relies upon the use of a convolutional neural network (CNN). The CNN architecture was constructed, followed by network learning on a balanced dataset composed of four classes of images, composed of thick and thin blood vessels, healthy areas, and exudate areas. The learning was conducted on 12x12 images because an experimental study showed them to be optimal for the purpose. The test error was no higher than 4% for all sizes of the samples. Segmentation of eye fundus images was performed using the CNN. Considering that exudates are a primary target of laser coagulation surgery, the segmentation error was calculated on the exudate class, amounting to 5%. In the course of this research, the HSL color system was found to be most informative, using which the segmentation error was reduced to 3%.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73348964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}