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Simple Character Recognition
Hamrský, Jan ; Svoboda, Pavel (referee) ; Polok, Lukáš (advisor)
This work deals with the process of text location and recognition in an image document. It discusses the matter of feature extraction and its usage in machine learning. Portion of this work is devoted to design and implementation of application for simple character recognition of machine printed text.
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A Tool for Analysis of User's Typing Skills
Moltaš, Jaroslav ; Szőke, Igor (referee) ; Herout, Adam (advisor)
This master's thesis deals with analysis of user's typing skills in Windows system. Touch method technique for fast keyboard typing is described. The possibilities of Windows keyboard hooking and GUI making are mentioned. The description of segmentation of written text and writing level evaluation techniques are part of this thesis. Another part deals with the system implementation. The result application collects data about user's typing skills and evaluates the quality of typing and number of mistakes.
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Web Document Annotator
Hrúz, Tomáš ; Hynek, Jiří (referee) ; Burget, Radek (advisor)
The goal of this bachelor thesis is to compare of tools for annotation of web documents and create module for experimental tool FitLayout, which implements required functionality for annotation. Solution was developed with the progressive framework Vue.js and with knowledge obtained by comparison of existing annotation tools. The output of the work is new stand-alone component and other component with added functionality in FitLayout application. The result of the work is the web application module for creating new areas in documents and adjusted module for managing comments and tags.
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Handwritten Character Recognition Using Artificial Neural Networks
Smejkal, Vojtěch ; Fapšo, Michal (referee) ; Plchot, Oldřich (advisor)
Thesis deals with handwritten block letters and digits recognition using artificial neural networks. Text segmentation algorithms, feature extraction methods and backpropagation learning are explained. There are also described performed experiments with variety of configurations on datasets. Application with graphical user interface and interactive mouse-written text recognition was created to train new neural networks and test their effectivity.
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Optical Character Recognition
Suchý, Václav ; Kršek, Přemysl (referee) ; Španěl, Michal (advisor)
This paper describes problems of text recognition in picture. Discuss successes, advatages and disadvantages several methods of recognition. In second part there is described design and implementation of a simple OCR software for typewritten text recognition by using artificial neural networks.
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Text recognition with artificial neural networks
Peřinová, Barbora ; Hesko, Branislav (referee) ; Mézl, Martin (advisor)
This master’s thesis deals with optical character recognition. The first part describes the basic types of optical character recognition tasks and divides algorithm into individual phases. For each phase the most commonly used methods are described in the next part. Within the character recognition phase the problematics of artificial neural networks and their usage in given phase is explained, specifically multilayer perceptron and convolutional neural networks. The second part deals with requirements definition for specific application to be used as feedback for robotic system. Convolution neural networks and CNTK library for deep learning using algorithm implementation in .NET is introduced. Finally, the test results of the individual phases of the proposed solution and the comparison with the open source Tesseract engine are discussed.
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Web Document Annotator
Hrúz, Tomáš ; Hynek, Jiří (referee) ; Burget, Radek (advisor)
The goal of this bachelor thesis is to compare of tools for annotation of web documents and create module for experimental tool FitLayout, which implements required functionality for annotation. Solution was developed with the progressive framework Vue.js and with knowledge obtained by comparison of existing annotation tools. The output of the work is new stand-alone component and other component with added functionality in FitLayout application. The result of the work is the web application module for creating new areas in documents and adjusted module for managing comments and tags.
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Text recognition with artificial neural networks
Peřinová, Barbora ; Hesko, Branislav (referee) ; Mézl, Martin (advisor)
This master’s thesis deals with optical character recognition. The first part describes the basic types of optical character recognition tasks and divides algorithm into individual phases. For each phase the most commonly used methods are described in the next part. Within the character recognition phase the problematics of artificial neural networks and their usage in given phase is explained, specifically multilayer perceptron and convolutional neural networks. The second part deals with requirements definition for specific application to be used as feedback for robotic system. Convolution neural networks and CNTK library for deep learning using algorithm implementation in .NET is introduced. Finally, the test results of the individual phases of the proposed solution and the comparison with the open source Tesseract engine are discussed.
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Optical Character Recognition
Suchý, Václav ; Kršek, Přemysl (referee) ; Španěl, Michal (advisor)
This paper describes problems of text recognition in picture. Discuss successes, advatages and disadvantages several methods of recognition. In second part there is described design and implementation of a simple OCR software for typewritten text recognition by using artificial neural networks.
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