Trudy Instituta sistemnogo programmirovaniia RAN最新文献_第10页

Organization of a secure query to a database in the cloud 组织对云中的数据库的安全查询

Trudy Instituta sistemnogo programmirovaniia RAN Pub Date : 2022-01-01 DOI: 10.15514/ispras-2022-34(3)-12

S. Martishin, M. V. Khrapchenko, A. Shokurov

引用次数: 0

Automatic data labeling for document image segmentation using deep neural networks 基于深度神经网络的文档图像分割自动数据标注

Trudy Instituta sistemnogo programmirovaniia RAN Pub Date : 2022-01-01 DOI: 10.15514/ispras-2022-34(6)-10

Andrey Anatolievitch Mikhaylov

{"title":"Automatic data labeling for document image segmentation using deep neural networks","authors":"Andrey Anatolievitch Mikhaylov","doi":"10.15514/ispras-2022-34(6)-10","DOIUrl":"https://doi.org/10.15514/ispras-2022-34(6)-10","url":null,"abstract":"The article proposes a new method for automatic data annotation for solving the problem of document image segmentation using deep object detection neural networks. The format of marked PDF files is considered as the initial data for markup. The peculiarity of this format is that it includes hidden marks that describe the logical and physical structure of the document. To extract them, a tool has been developed that simulates the operation of a stack-based printing machine according to the PDF format specification. For each page of the document, an image and annotation are generated in PASCAL VOC format. The classes and coordinates of the bounding boxes are calculated during the interpretation of the labeled PDF file based on the labels. To test the method, a collection of marked up PDF files was formed from which images of document pages and annotations for three segmentation classes (text, table, figure) were automatically obtained. Based on these data, a neural network of the EfficientDet D2 architecture was trained. The model was tested on manually labeled data from the same domain, which confirmed the effectiveness of using automatically generated data for solving applied problems.","PeriodicalId":33459,"journal":{"name":"Trudy Instituta sistemnogo programmirovaniia RAN","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85806570","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}

引用次数: 0

Big Transformers for Code Generation 代码生成的大变形器

Trudy Instituta sistemnogo programmirovaniia RAN Pub Date : 2022-01-01 DOI: 10.15514/ispras-2022-34(4)-6

erman Arsenovich Arutyunov, S. Avdoshin

引用次数: 1

Automated testing of LLVM programs with complex input data structures 具有复杂输入数据结构的LLVM程序的自动测试

Trudy Instituta sistemnogo programmirovaniia RAN Pub Date : 2022-01-01 DOI: 10.15514/ispras-2022-34(4)-4

Alexander Vladimirovich Misonizhnik, A. A. Babushkin, S. Morozov, Yu.O. Kostyukov, D. Mordvinov, D. Koznov

引用次数: 1

Group Cohesion for a Coaching System in Co-located Collaborative Environments 协同环境下教练系统的团队凝聚力

Trudy Instituta sistemnogo programmirovaniia RAN Pub Date : 2022-01-01 DOI: 10.15514/ispras-2022-34(3)-8

Alessandra R eyes-Flores, Carmen Mezura-Godoy, E. Benítez-Guerrero, Luis Gerardo Montané-Jiménez

引用次数: 0

Wi-Fi sensing Human Detection with Kolmogorov-Wiener Filter and Gated Recurrent Neural Networks 基于Kolmogorov-Wiener滤波和门控递归神经网络的Wi-Fi传感人体检测

Trudy Instituta sistemnogo programmirovaniia RAN Pub Date : 2022-01-01 DOI: 10.15514/ispras-2022-34(2)-11

P. Shibaev, A. Chupakhin

引用次数: 0

Combined method for plagiarism detection in text documents 文本文档中抄袭检测的组合方法

Trudy Instituta sistemnogo programmirovaniia RAN Pub Date : 2022-01-01 DOI: 10.15514/ispras-2022-34(1)-11

Kamil Safin, Y. Chehovich

{"title":"Combined method for plagiarism detection in text documents","authors":"Kamil Safin, Y. Chehovich","doi":"10.15514/ispras-2022-34(1)-11","DOIUrl":"https://doi.org/10.15514/ispras-2022-34(1)-11","url":null,"abstract":"There are two global approaches to the problem of searching plagiarism in the text: external and intrinsic search. The first approach implies search through an external collection of documents that could have been used for text reuse. The second approach, on the contrary, does not use any external data, but analyzes the text by itself. It is proposed to combine these two approaches to speed up the search for text plagiarism. With a large flow of documents that need to be checked, the outer corpus search system processes each document and finds plagiarised blocks in each document, if there are any. However, intrinsic search could be used to determine the fact of plagiarism. Thus, it is possible to reduce the number of documents for the expensive procedure for searching for plagiarism by the outer corpus. Moreover, in an isolated analysis of a single document, there is no need to try to find specific blocks of plagiarism, this procedure is considered as a unique indicator of the originality of the document. If the overall originality is at a low level, then this document should be sent for a more detailed and accurate check. The proposed method allows to filter texts with a high rate of originality that do not need additional verification.","PeriodicalId":33459,"journal":{"name":"Trudy Instituta sistemnogo programmirovaniia RAN","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81352020","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}

引用次数: 1

Research Perspectives on the Tatar language based on the LingvoDoc platform 基于LingvoDoc平台的鞑靼语研究展望

Trudy Instituta sistemnogo programmirovaniia RAN Pub Date : 2022-01-01 DOI: 10.15514/ispras-2022-34(6)-13

F. Nurieva, G. Galiullina, A. F. Yusupov

{"title":"Research Perspectives on the Tatar language based on the LingvoDoc platform","authors":"F. Nurieva, G. Galiullina, A. F. Yusupov","doi":"10.15514/ispras-2022-34(6)-13","DOIUrl":"https://doi.org/10.15514/ispras-2022-34(6)-13","url":null,"abstract":"The article discusses research perspectives on the Tatar language based on the LingvoDoc platform. Digitalization of language learning in modern linguistics allows us to move to a new level of describing the language structure. Large corpora containing millions of word forms have been created in all European languages since the 90s of the last century. Currently, this has been done not only in the Russian language, but also in many national languages of Russia such as Tatar, Bashkir, Udmurt, Mari, Moksha, Komi, etc. One of the recognized platforms in modern national linguistics is the development of the LingvoDoc virtual laboratory, created ISP RAS. This platform gives an opportunity to create, store and analyze multilayer dictionaries, language materials and dialects. The main functionality of Lingvodoc is used by more than 250 linguists who process their materials online, more than 1000 dictionaries and 300 text corpora in the national languages of the Russian Federation have already been collected. We consider the possibilities of this platform to study the Tatar language. We believe that electronic corpora allow us to solve a variety of theoretical and practical problems of the language. At present, when the Tatar literary and everyday spoken language is actively used in all fields, it is very important to make a complete description of its features, which will help create more accurate grammars and dictionaries. The relevance of the study is due to the need to use a gloss corpus of texts in the Tatar language. As modern studies in linguistics show, nowadays it is impossible to describe the state of the language without such corpora and analyze its grammatical structure, which corresponds to the world standards of modern science. The LingvoDoc platform makes it possible to process a significant amount of material in a short time and create corpora with glossing and removed homonymy based on samples of the Tatar literary, business, colloquial and dialect languages.","PeriodicalId":33459,"journal":{"name":"Trudy Instituta sistemnogo programmirovaniia RAN","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85649924","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}

引用次数: 0

Detection of uses of disposed resources in C# source code using static analysis 使用静态分析检测c#中已处置资源的使用情况

Trudy Instituta sistemnogo programmirovaniia RAN Pub Date : 2022-01-01 DOI: 10.15514/ispras-2022-34(6)-3

Uljana Vladimirovna Tsiazhkorob, V. N. Ignatyev, A. Belevantsev

引用次数: 0

Overapproximation of the Number of Active Timers in Timed-Arc Petri Nets Using DP-Systems 用dp系统对定时弧Petri网中活动定时器数目的过逼近

Trudy Instituta sistemnogo programmirovaniia RAN Pub Date : 2022-01-01 DOI: 10.15514/ispras-2022-34(5)-12

L. W. Dworzanski

引用次数: 0