Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-219-226
L. E. Sapozhnikova, O. Gordeeva
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.
{"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":null,"pages":null},"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}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-222-232
E. Dremov, S. Miroshnichenko, V. Titov
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.
{"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":null,"pages":null},"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}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-283-289
E. Zguralskaya
The study is conducted to assess the compactness of descriptions of objects of classes on the numerical axis and in the multidimensional attribute space. The computation of compactness is possible only in the defined boundaries of areas of the attribute space. In the one-dimensional case, the boundaries are calculated by the frequency of occurrence of the values of features of objects of classes in the interval. In the multidimensional case, a subset of the boundary objects of the classes is used for a given metric. A comparative analysis is given of the values of the compactness measure by latent attributes on the numerical axis and by the sets of initial features from which they are synthesized.
{"title":"Analysis of the structure of the relationship between the descriptions of objects of classes and evaluation of their compactness","authors":"E. Zguralskaya","doi":"10.18287/1613-0073-2019-2416-283-289","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-283-289","url":null,"abstract":"The study is conducted to assess the compactness of descriptions of objects of classes on the numerical axis and in the multidimensional attribute space. The computation of compactness is possible only in the defined boundaries of areas of the attribute space. In the one-dimensional case, the boundaries are calculated by the frequency of occurrence of the values of features of objects of classes in the interval. In the multidimensional case, a subset of the boundary objects of the classes is used for a given metric. A comparative analysis is given of the values of the compactness measure by latent attributes on the numerical axis and by the sets of initial features from which they are synthesized.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78396262","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}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-371-379
A. Egorova, V. Fedoseev
This paper considers the applicability of different data embedding methods for semifragile watermarking systems used for JPEG image authentication. The methods include Least Significant Bit watermarking and various versions of Quantization Index Modulation. In our investigations, we tested the semi-fragility property against JPEG and compared the visual quality of the watermarked images. We also checked the watermark fragility to unacceptable modifications like median filtering, blurring, and adding Gaussian noise. Finally, we analyzed the provided tampering localization error.
{"title":"Evaluation of different embedding methods for JPEG authentication watermarking","authors":"A. Egorova, V. Fedoseev","doi":"10.18287/1613-0073-2019-2391-371-379","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-371-379","url":null,"abstract":"This paper considers the applicability of different data embedding methods for semifragile watermarking systems used for JPEG image authentication. The methods include Least Significant Bit watermarking and various versions of Quantization Index Modulation. In our investigations, we tested the semi-fragility property against JPEG and compared the visual quality of the watermarked images. We also checked the watermark fragility to unacceptable modifications like median filtering, blurring, and adding Gaussian noise. Finally, we analyzed the provided tampering localization error.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74192542","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}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-141-148
M. N. Mokrousov
The article describes a solution to the problem of word separation in old Cyrillic texts after the stage of graphic character recognition on scanned documents. The article proposes an algorithm for fuzzy text search using the grammatical dictionary of the Old Russian language, with the completeness and accuracy of search results evaluate. To assess the relevance and ranking of the search results, a method for calculating the rank of the symbol recognition variant based on the TF-IDF metric is developed. The article also presents a software system of automated word search, presents the results of experiments that prove the effectiveness of the developed algorithms and programs.
{"title":"The words separation in old Cyrillic texts with fuzzy search method","authors":"M. N. Mokrousov","doi":"10.18287/1613-0073-2019-2416-141-148","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-141-148","url":null,"abstract":"The article describes a solution to the problem of word separation in old Cyrillic texts after the stage of graphic character recognition on scanned documents. The article proposes an algorithm for fuzzy text search using the grammatical dictionary of the Old Russian language, with the completeness and accuracy of search results evaluate. To assess the relevance and ranking of the search results, a method for calculating the rank of the symbol recognition variant based on the TF-IDF metric is developed. The article also presents a software system of automated word search, presents the results of experiments that prove the effectiveness of the developed algorithms and programs.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73772158","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}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-175-179
A. Burlakov, A. Machikhin, D. Khokhlov, V. Kuzmin, A. F. Gadzaov, D. L. Tytik, S. Busev, V. Kasatkin, L. Sleptsova
Studying the embryo development at an early stage is considered. For this, hyperspectral imaging using an acousto-optical microscope-based system is proposed. Acousto-optic visualization of the early developmental stages of the loach Misgurnus fossilis embryo showed a regular change in the spectral characteristics of different image areas corresponding to the tissues and body fluids, depending on the functional state of the embryo. We show that there is a discrete set of maxima in the optical absorption spectrum with a distance of 20 nm and 30 nm between them. Value 20 nm corresponds to the normal development of biological tissue. The appearance of the value 30 nm between the maxima of neighboring optical absorption bands indicates the development of pathological processes in the biosystem. Such deviations from the norm are characteristic of germinal tissues, and they are absent in the perivitelline fluid. Thus, we demonstrated that for the early diagnosis of the physiological state of a developing biosystem, special attention should be paid to optical absorption spectra.
{"title":"Early diagnosis of a developing biosystem using acousto-optic imaging","authors":"A. Burlakov, A. Machikhin, D. Khokhlov, V. Kuzmin, A. F. Gadzaov, D. L. Tytik, S. Busev, V. Kasatkin, L. Sleptsova","doi":"10.18287/1613-0073-2019-2391-175-179","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-175-179","url":null,"abstract":"Studying the embryo development at an early stage is considered. For this, hyperspectral imaging using an acousto-optical microscope-based system is proposed. Acousto-optic visualization of the early developmental stages of the loach Misgurnus fossilis embryo showed a regular change in the spectral characteristics of different image areas corresponding to the tissues and body fluids, depending on the functional state of the embryo. We show that there is a discrete set of maxima in the optical absorption spectrum with a distance of 20 nm and 30 nm between them. Value 20 nm corresponds to the normal development of biological tissue. The appearance of the value 30 nm between the maxima of neighboring optical absorption bands indicates the development of pathological processes in the biosystem. Such deviations from the norm are characteristic of germinal tissues, and they are absent in the perivitelline fluid. Thus, we demonstrated that for the early diagnosis of the physiological state of a developing biosystem, special attention should be paid to optical absorption spectra.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79305249","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}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-314-323
V. Blinov, S. Valeev, N. Kondratyeva, R. Karimov, Alexey S. Kovtunenko, E. Kuzmina
The application of predictive analytics in the design, production and operation to achieve the efficiency of the life cycle of complex technical systems is discussed. A predictive model of information support for the life cycle of a microsatellite propulsion system based on a neural network system is proposed. The predictive model can solve the problem of estimating fuel consumption, diagnosing and detecting possible failures of a small propulsion system.
{"title":"Supporting the life cycle of complex technical systems on the basis of intelligent technologies and predictive analytics","authors":"V. Blinov, S. Valeev, N. Kondratyeva, R. Karimov, Alexey S. Kovtunenko, E. Kuzmina","doi":"10.18287/1613-0073-2019-2416-314-323","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-314-323","url":null,"abstract":"The application of predictive analytics in the design, production and operation to achieve the efficiency of the life cycle of complex technical systems is discussed. A predictive model of information support for the life cycle of a microsatellite propulsion system based on a neural network system is proposed. The predictive model can solve the problem of estimating fuel consumption, diagnosing and detecting possible failures of a small propulsion system.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79432854","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}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-158-164
P. Katkov, N. Davydov, A. Khramov, A. Nikonorov
In this paper, the use of artificial neural networks for the myocardial infarction diagnosis is investigated. For the analysis, 169 ECG records were taken from the database of the Massachusetts University of Technology, of which 80 correspond to healthy patients and 89 correspond to patients who have a myocardial infarction. Each signal has been preprocessed. The result of preprocessing each signal is a common segment consisting of 1000 samples. To detect myocardial infarction, a convolutional neural network consisting of two convolutional layers was used. For accuracy of the neural network leave-one-out crossvalidation was used. The best results of the experiments are obtained with the neural network for leads V1, V2, AVF.
{"title":"Research on the use of artificial neural networks for the myocardial infarction diagnosis","authors":"P. Katkov, N. Davydov, A. Khramov, A. Nikonorov","doi":"10.18287/1613-0073-2019-2416-158-164","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-158-164","url":null,"abstract":"In this paper, the use of artificial neural networks for the myocardial infarction diagnosis is investigated. For the analysis, 169 ECG records were taken from the database of the Massachusetts University of Technology, of which 80 correspond to healthy patients and 89 correspond to patients who have a myocardial infarction. Each signal has been preprocessed. The result of preprocessing each signal is a common segment consisting of 1000 samples. To detect myocardial infarction, a convolutional neural network consisting of two convolutional layers was used. For accuracy of the neural network leave-one-out crossvalidation was used. The best results of the experiments are obtained with the neural network for leads V1, V2, AVF.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79732969","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}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2416-119-125
V. Tsvetov
Algebras of finitary relations naturally generalize the algebra of binary relations with the left composition. In this paper, we consider some properties of such algebras. It is well known that we can study the hypergraphs as finitary relations. In this way the results can be applied to graph and hypergraph theory, automatons and artificial intelligence.
{"title":"Algebras of finitary relations","authors":"V. Tsvetov","doi":"10.18287/1613-0073-2019-2416-119-125","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2416-119-125","url":null,"abstract":"Algebras of finitary relations naturally generalize the algebra of binary relations with the left composition. In this paper, we consider some properties of such algebras. It is well known that we can study the hypergraphs as finitary relations. In this way the results can be applied to graph and hypergraph theory, automatons and artificial intelligence.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85330268","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}
Pub Date : 2019-01-01DOI: 10.18287/1613-0073-2019-2391-86-96
R. Dosaev, K. Kiy
In this paper, a new real-time method for finding temporary and permanent road marking is proposed. The method is based on the geometrized histograms method for segmenting and describing color images. This method is able to deal with both rectilinear and curvilinear marking, as well as with color temporary and permanent road marking. It also makes it possible to distinguish temporary road marking from white permanent road marking. The developed method is stable under illumination and is able to work even for partially disappearing road marking, typical for late winter and early spring. In contrast to many other methods, this method does not require any information about camera parameters and calibration and is able to find road marking in images taken under unknown conditions. The proposed method has been implemented by a program written in C++, operating under Windows and Linux. The program operation has been tested on video records shot on typical Russian roads during different seasons and under diverse whether and illumination conditions. The processing speed is about 20 fps for a standard modern computer. Using parallel computing, this speed is reduced considerably. The results of program operation are presented and discussed. The developed program is a part of the computer vision component of the control system of the AvtoNiva pilotless vehicle.
{"title":"A new real-time method for finding temporary and permanent road marking and its applications","authors":"R. Dosaev, K. Kiy","doi":"10.18287/1613-0073-2019-2391-86-96","DOIUrl":"https://doi.org/10.18287/1613-0073-2019-2391-86-96","url":null,"abstract":"In this paper, a new real-time method for finding temporary and permanent road marking is proposed. The method is based on the geometrized histograms method for segmenting and describing color images. This method is able to deal with both rectilinear and curvilinear marking, as well as with color temporary and permanent road marking. It also makes it possible to distinguish temporary road marking from white permanent road marking. The developed method is stable under illumination and is able to work even for partially disappearing road marking, typical for late winter and early spring. In contrast to many other methods, this method does not require any information about camera parameters and calibration and is able to find road marking in images taken under unknown conditions. The proposed method has been implemented by a program written in C++, operating under Windows and Linux. The program operation has been tested on video records shot on typical Russian roads during different seasons and under diverse whether and illumination conditions. The processing speed is about 20 fps for a standard modern computer. Using parallel computing, this speed is reduced considerably. The results of program operation are presented and discussed. The developed program is a part of the computer vision component of the control system of the AvtoNiva pilotless vehicle.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84094633","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}
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