Segmentation of vasculature tree is an important step of the process of image processing. There are many methods of automatic blood vessel segmentation. These methods are based on matched filters, pattern recognition or image classification. Use of automatic retinal image processing greatly simplifies and accelerates retinal images diagnosis. The aim of the automatic image segmentation algorithms is thresholding. This work primarily deals with retinal image thresholding. We discuss a few works using local and global image thresholding and supervised image classification to segmentation of blood tree from retinal images. Subsequently is to set of results from two different methods used image classification and discuss effectiveness of the vessel segmentation. Use image classification instead of global thresholding changed statistics of first method on healthy part of HRF. Sensitivity and accuracy decreased to 62,32 %, respectively 94,99 %. Specificity increased to 95,75 %. Second method achieved sensitivity 69.24 %, specificity 98.86% and 95.29 % accuracy. Combining the results of both methods achieved sensitivity up to72.48%, specificity to 98.59% and the accuracy to 95.75%. This confirmed the assumption that the classifier will achieve better results. At the same time, was shown that extend the feature vector combining the results from both methods have increased sensitivity, specificity and accuracy.

Abstract The theoretical part of the thesis entitled The Use of NIC and NOC Classifications at Patients with the Total Hip Arthroplasty deals with the problem of the total hip replacement, educating patients before surgery and the regime which must be observed by the patient during the hospitalization and when being discharged from the hospital to home nursing. Further, the nurse has been described as a provider of rehabilitation nursing cooperating with the physiotherapist. The thesis is concerned with the nursing process, it preoccupies with the terminology in the health care, the issue of NANDA, NIC and NOC classifications and the Alliance 3N. Three goals of the thesis were defined: 1. to find out what types of NIC activities are typically used by nurses within the care of patients with total hip replacement. 2. to verify the application of NIC an NOC classifications in the care of patients with total hip replacement. 3. to investigate what sorts of the NOC indicators are typically used by the nurses in the care of patients with total hip replacement. The combination of the quantitative and qualitative research is applied. The four hypotheses were determined in the frame of the quantitative survey: 1. Nursing diagnoses are assessed as not being beneficial by the nurses. 2. Ensuring of tools facilitating the movement is a commonly preferred kind of an intervention by the nurses. 3. The knowledge of NIC and NOC terms is influenced by the previous education. 4. The satisfaction of the nurses with the nursing documentation is influenced by the length of practice. Data was collected by means of the questionnaires. One research query was established for the qualitative research: 1. What is the standpoint of the nurses on the NIC and NOC classifications in the care of the patient with total hip replacement? Data was collected by means of the formed nursing documentation based on the NIC and NOC classifications. The semi-structured interviews were used, as well. H1 remained unconfirmed. H2, H3 and H4 were not statistically validated. The NIC and NOC classifications are generally classified as not being beneficial for the nursing practice by the nurses.

In this thesis is handled the problem of mushroom detection and recognition in natural environment. Convolutional neural networks are used. The beginning of this thesis is dedicated to the theory of neural networks. Further is solved the problem of object detection and classification. Using neural network trained for classification is solved also the task of localization. Results of trained CNNs are analised.

The PhD thesis deals with modern methods of image processing, especially image segmentation, classification and evaluation of parameters. It is focused primarily on processing medical images of soft tissues obtained by magnetic resonance tomography (MR) and microscopic images of tissues. It is easy to describe edges of the sought objects using of segmented images. The edges found can be useful for further processing of monitored object such as calculating the perimeter, surface and volume evaluation or even three-dimensional shape reconstruction. The proposed solutions can be used for the classification of healthy/unhealthy tissues in MR or other imaging. Application examples of the proposed segmentation methods are shown in this thesis. Research in the area of image segmentation is focused on methods based on solving partial differential equations. This is a modern method for image processing, often called the active contour method. It is of great advantage in the segmentation of real images degraded by noise with fuzzy edges and transitions between objects. The results of the thesis are methods proposed for automatic image segmentation and classification.

This work deals with methods of web page classification. It explains the concept of classification and different features of web pages used for their classification. Further it analyses representation of a page and in detail describes classification method that deals with hierarchical category model and is able to dynamically create new categories. In the second half it shows implementation of chosen method and describes the results.

Knowledge discovery in text documents is part of data mining. However, text documents have different properties in comparison to regular databases. This project contains an overview of methods for knowledge discovery in text documents. The most frequently used task in this area is document classification. Various approaches for text classification will be described. Finally, I will present algorithm Winnow that should perform better than any other algorithm for classification. There is a description of Winnow implementation and an overview of experimental results.

This diploma thesis deals with the data mining and the creation of data mining unit for data mining system, which is beeing developed at FIT. This is a client application consisting of a kernel and its graphical user interface and independent mining modules. The application uses support of Oracle Data Mining. The data mining system is implemented in Java language and its graphical user interface is built on NetBeans platform. The content of this work will be the introduction into the issue of knowledge discovery and then the presentation of the chosen Bayesian classification method, for which there will subsequently be implemented the stand-alone data mining module. Furthermore, the implementation of this module will be described.

Spinning-particle motion is studied, within the pole-dipole approximation, in algebraically special space-times of type N, III and D. The spin-curvature interaction is analysed for the Pirani and Tulczyjew spin supplementary conditions; for N and D types, the condition is related to a relative acceleration of two near observers separated in the direction of particle's spin. For Tulczyjew's condition, the momentum-velocity relation is also studied as well as its consequences for the spin-curvature interaction. Finally, the type of motion is mentioned for which both the supplementary conditions considered are equivalent.

Title: Emotional reactions of young people to school physical education Objectives: The main objective of this work is to determine and compare the emotional reactions of pupils during the sport lessons on secondary schools. We focus on the seventh and eighth graders, boys and girls at the age from twelve to fourteen. The goal is to statistically process and compare the results between the genders and between schools in urban and rural areas. Determine the reliability and internal consistency of the items from the individual factors in the selected DEMOR questionnaire. Evaluate the determined data in synoptic tables and graphs. Methods: The method of questioning was used in this work. To meet the objectives we analysed the responses obtained from the DEMOR questionnaire. Through this survey, it is possible to record the emotional reactions of the pupils and their perceptions of experiences they had to get information about the climate during physical education lessons. The survey was conducted on twelve secondary schools in rural and urban areas in the Karlovy Vary region. Results: The results indicate that, positive feelings prevail in current physical education classes. We found only a very slight difference in positive and negative feelings among the schools in rural and urban areas....

The master thesis deals with subpixel classification of hyperspectral data from senzor APEX. In the first part there is research from the literature describing algorithms of the subpixel classifications and spectral characteristics of the vegetation. In the practical part there is a work focusing on the classification of the areas with the cover of Norway Spruce trees at eight areas in the Krkonoše national park. Three methods of supervised classification were used - Linear Spectral Unmixing, Support Vector Machine and Spectral Angle Mapper. Field data, spectral curves for exact trees from the eight areas obtained by the contact probe ASD FieldSpec 4 Wide-Res, were used for the extraction of endmembers of the spruces. For each research area maps of land cover were produced by means of the classification methods described above and the accuracies of the classifications were evaluated. Powered by TCPDF (www.tcpdf.org)