Open Access
Application of Methods of Machine Learning for the Recognition of Mathematical Expressions.
Oleh Veres,Ihor Rishnyak,Halyna Rishniak +2 more
- pp 378-389
TLDR
The article describes the study of the peculiarities of presentation of mathematical methods, as well as methods and algorithms for their recognition, and the possibility of simultaneous execution of structural analysis and character classification is investigated.Abstract:
The article describes the study of the peculiarities of presentation of mathematical methods, as well as methods and algorithms for their recognition. The possibility of simultaneous execution of structural analysis and character classification is investigated. The process of classification of the symbols and construction of the corresponding system, based on methods of machine learning, is described. For the initial initialization of the symbol classification process, a segmented binary image passes a "rough" classification by the Bayesian Network. Classification using contexts is processed by artificial Neural Networks. The system being developed is a multi-classifier. Five different classifiers work to get the optimal result.read more
Citations
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Journal ArticleDOI
A retrospective study on handwritten mathematical symbols and expressions: Classification and recognition
Sakshi,Vinay Kukreja +1 more
TL;DR: In this paper, the authors performed an extensive state-of-the-art on the techniques and methods used for recognizing and classifying HMSE, and brought out all significant findings in sub-processes, representation models, algorithms, tools, datasets, and comparative analysis of the accuracy of the recognition models.
Methods and Models of Intellectual Processing of Texts for Building Ontologies of Software for Medical Terms Identification in Content Classification.
Vasyl Lytvyn,Yevhen Burov,Petro Kravets,Victoria Vysotska,Andriy Demchuk,Andrii Berko,Yuriy Ryshkovets,Serhii Shcherbak,Oleh Naum +8 more
TL;DR: Methods and models of intellectual text processing are examined, the results of which are intended to build software ontologies, and are used during Ontology Learning, when it is necessary to improve, extend, modify an existing ontology model, or build ontology from basic ontology, having only text collections as sources of knowledge.
Information System for Recommendation List Formation of Clothes Style Image Selection According to User's Needs Based on NLP and Chatbots.
TL;DR: The purpose of this work is to develop software so that chat bot will be function on Telegram messenger base and archive a high level of natural user language recognition that increased interactivity and communication is connected.
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TL;DR: This project will help to omit difficult and long-lasting phone calls, automate and optimize flight plan rendering, provide with high data accuracy, and ensure easy and fast itinerary scheduling around the most problematical areas of Europe.
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Vasyl Lytvyn,Victoria Vysotska,Nataliya Shakhovska,Vladyslav Mykhailyshyn,Mykola Medykovskyy,Ivan Peleshchak,Vítor Basto Fernandes,Roman Peleshchak,Serhii Shcherbak +8 more
TL;DR: The intelligent system of a smart house, which is designed to create from any house, office, or building a smart room, was created in the overall process, and the experience of analogues was used while the designing and development of the system, and a lot of problems were avoided.
References
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Computer vision
TL;DR: How the field of computer (and robot) vision has evolved, particularly over the past 20 years, is described, and its central methodological paradigms are introduced.
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Computer Vision
George Stockman,Linda G. Shapiro +1 more
TL;DR: Computer Vision presents the necessary theory and techniques for students and practitioners who will work in fields where significant information must be extracted automatically from images, a useful resource book for professionals and a core text for both undergraduate and beginning graduate computer vision and imaging courses.
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Recognizing mathematical expressions using tree transformation
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Proceedings ArticleDOI
Mathematical formula recognition using virtual link network
Y. Eto,Masakazu Suzuki +1 more
TL;DR: A new method of recognizing mathematical formulae that is robust against the recognition errors of characters and the variation of the printing styles of the documents, and that local errors of the recognition are recovered automatically by the total cost of the Recognition tree.
Proceedings Article
Ambiguity and constraint in mathematical expression recognition
Erik G. Miller,Paul A. Viola +1 more
TL;DR: A new lower bound estimate on the cost to goal that improves performance significantly is provided and the system limits the number of potentially valid interpretations by decomposing the expressions into a sequence of compatible convex regions.