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Optical character recognition from image data
Marinič, Michal ; Uher, Václav (referee) ; Burget, Radim (advisor)
The thesis is concerned with optical character recognition from image data with different methods used for character classification. In the first theoretical part it focuses on explanation of all important parts of system for optical character recognition. The latter practical part of the thesis describes an example of image segmentation, the implementation of artificial neural networks for image recognition and create simple training set of data for the evaluation of the network. It also describes the process of training Tesseract tool and its implementation in a simple application EasyTessOCR for character recognition.
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Scalable preprocessing of data using Hadoop tool
Marinič, Michal ; Šmirg, Ondřej (referee) ; Burget, Radim (advisor)
The thesis is concerned with scalable pre-processing of data using Hadoop tool which is used for processing of large volumes of data. In the first theoretical part it focuses on explaining of functioning and structure of the basic elements of Hadoop distributed file system and MapReduce methods for parallel processing. The latter practical part of the thesis describes the implementation of basic Hadoop cluster in pseudo-distributed mode for easy program-debugging, and also describes an implementation of Hadoop cluster in fully-distributed mode for simulation in practice.
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Scalable preprocessing of data using Hadoop tool
Marinič, Michal ; Šmirg, Ondřej (referee) ; Burget, Radim (advisor)
The thesis is concerned with scalable pre-processing of data using Hadoop tool which is used for processing of large volumes of data. In the first theoretical part it focuses on explaining of functioning and structure of the basic elements of Hadoop distributed file system and MapReduce methods for parallel processing. The latter practical part of the thesis describes the implementation of basic Hadoop cluster in pseudo-distributed mode for easy program-debugging, and also describes an implementation of Hadoop cluster in fully-distributed mode for simulation in practice.
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|
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Optical character recognition from image data
Marinič, Michal ; Uher, Václav (referee) ; Burget, Radim (advisor)
The thesis is concerned with optical character recognition from image data with different methods used for character classification. In the first theoretical part it focuses on explanation of all important parts of system for optical character recognition. The latter practical part of the thesis describes an example of image segmentation, the implementation of artificial neural networks for image recognition and create simple training set of data for the evaluation of the network. It also describes the process of training Tesseract tool and its implementation in a simple application EasyTessOCR for character recognition.
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