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National Repository of Grey Literature 4 records found  Search took 0.01 seconds. 
Analysis of Dashboard Attributes Based on Automatic Decomposition of Screen
 Mejía, Santiago ; Rudnitckaia, Julia (referee) ; Hynek, Jiří (advisor)
The aim of this paper is to propose a method for automatic segmentation of dashboards so that they can be analyzed using aesthetic by means of metrics. These metrics analyze the properties of the screen objects by region. This method is based on bottom-up segmentation method and creates objects based on proximity. The main result is a faster and more accurate analysis of dashboards, as there is no need to manually segment the image.
Detailed record
Automatic Segmentation of Documents Stored as Images
 Jakub, Dušan ; Španěl, Michal (referee) ; Szőke, Igor (advisor)
This work deals with dividing the documents stored as images into three groups of segments - background, text and graphics. It introduces various solutions and the method using Gabor filters and artficial neural networks is described in detail. The selection of apropriate settings of the filters and training parameters of the network is discussed. Connected components searching is used for improving the results. A classifier writen in C++ and OpenCV library is part of the work. The designed procedure is applied for segmentation of scanned scientific papers, but also the results of segmentation of more complex documents (advertisements, presentation slides) are presented.
Detailed record
Analysis of Dashboard Attributes Based on Automatic Decomposition of Screen
 Mejía, Santiago ; Rudnitckaia, Julia (referee) ; Hynek, Jiří (advisor)
The aim of this paper is to propose a method for automatic segmentation of dashboards so that they can be analyzed using aesthetic by means of metrics. These metrics analyze the properties of the screen objects by region. This method is based on bottom-up segmentation method and creates objects based on proximity. The main result is a faster and more accurate analysis of dashboards, as there is no need to manually segment the image.
Detailed record
Automatic Segmentation of Documents Stored as Images
 Jakub, Dušan ; Španěl, Michal (referee) ; Szőke, Igor (advisor)
This work deals with dividing the documents stored as images into three groups of segments - background, text and graphics. It introduces various solutions and the method using Gabor filters and artficial neural networks is described in detail. The selection of apropriate settings of the filters and training parameters of the network is discussed. Connected components searching is used for improving the results. A classifier writen in C++ and OpenCV library is part of the work. The designed procedure is applied for segmentation of scanned scientific papers, but also the results of segmentation of more complex documents (advertisements, presentation slides) are presented.
Detailed record

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