National Repository of Grey Literature 17 records found  1 - 10next  jump to record: Search took 0.01 seconds. 
2D Texture Features
Pasáček, Václav ; Šiler, Ondřej (referee) ; Švub, Miroslav (advisor)
Because texture of object is very valuable information in computer vision, it is important to describe it somehow. And for this serve texture features. Optimal selection of features is very important for recognizing texture. In this bachelor thesis were used local binary patterns (LBP) as a method of gaining texture feature. In this method is not its value the texture feature, but histogram of percent occurrence values in the entire texture. To compare histograms there is used Euclidean distance, Bhattacharyya distance or Mahalanobis distance. Main purpose of this thesis is mutually comparing of texture clasification by several variants of LBP and evaluation of their outcomes by Euclidean distance, Bhattacharyya distance or Mahalanobis distance.
Algorithms for anomaly detection in data from clinical trials and health registries
Bondarenko, Maxim ; Blaha, Milan (referee) ; Schwarz, Daniel (advisor)
This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.
Water Object Detection in Image
Čeloud, David ; Španěl, Michal (referee) ; Šilhavá, Jana (advisor)
Bachelor's thesis describes history of remote sensing, image data structure, their processing and analyzing. It defines mulstispectral space and explains basics of quantitative analysis and  differences between supervised and unsupervised classification. Implementation section describes designing and developing of program, which will be able to open and process image data and detect water objects in him.
Cluster Analysis
Chrobák, Martin ; Ronzhina, Marina (referee) ; Kozumplík, Jiří (advisor)
This master’s thesis is engaged in usage of cluster analysis for ECG signal to separate normal QRS complexes from abnormal ones. For this, it is used two algorithms created in professional computing interface MATLAB. The outputs from this master’s thesis are dendrograms, which divide QRS complexes into abnormal and normal clusters, and Pearson correlation coefficients.
Algorithms for anomaly detection in data from clinical trials and health registries
Bondarenko, Maxim ; Blaha, Milan (referee) ; Schwarz, Daniel (advisor)
This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.
Homology search using digital signal processing methods
Kamar, Yana ; Jugas, Robin (referee) ; Maděránková, Denisa (advisor)
Thesis includes the theoretical introduction to molecular biology and genetics on the necessary level, including a description of the structure of DNA and the homologous gene. Described are fixed and physic-chemical kinds of nucleotide mapping, methods for processing digital signals. Numerical representations of genes that were programmed in MATLAB: unwrapped and accumulated phases, density vectors. Using the unwrapped phase and density vectors with windows of different lengths was performed CDS searching in the entire genome by calculation metric distances (euclidean and canberian) and correlation. Also, using the metric distances, a homologous gene was found in more or less similar bacterial genomes. The result is the approximate threshold of distance (euclidean and canberian) using to find homologous genes in genome.
Dynamic Time Warping in Biosignal Processing
Kubát, Milan ; Kozumplík, Jiří (referee) ; Klimek, Martin (advisor)
This work is dedicated to dynamic time warping in biosignal processing, especially it´s application for ECG signals. On the beginning the theoretical notes about cardiography are summarized. Then, the DTW analysis follows along with conditions and demands assessments for it’s successful application. Next, several variants and application possibilities are described. The practical part covers the design of this method, the outputs comprehension, settings optimization and realization of methods related with DTW
Cluster Analysis of ECG Signals
Dvořáček, Tomáš ; Chrobák, Martin (referee) ; Kozumplík, Jiří (advisor)
This bachelor thesis is engaged in problematics of automatic cluster analysis for ECG sinals. This bachelor thesis contains theory of pathology in cardiac rhythm and problematics of cluster analysis. Based on a gained knowledge, set of symptoms is made, which are used for cluster analysis using MATLAB interface and which results are evaluated.
Distribution of interpoint distances
Horská, Šárka ; Hlávka, Zdeněk (advisor) ; Komárek, Arnošt (referee)
This thesis investigates basic properties of the interpoint distances be- tween random vectors drawn from multinomial distribution. We also describe a possible application to testing sparse observations, i.e., a setup with small number of observations and large number of categories, where the classical χ2 -test cannot be recommended. As an alternative, utilizing the multinomial interpoint distances, we will present the test statistic proposed by Biswas and Ghosh (2014). 1
Algorithms for anomaly detection in data from clinical trials and health registries
Bondarenko, Maxim ; Blaha, Milan (referee) ; Schwarz, Daniel (advisor)
This master's thesis deals with the problems of anomalies detection in data from clinical trials and medical registries. The purpose of this work is to perform literary research about quality of data in clinical trials and to design a personal algorithm for detection of anomalous records based on machine learning methods in real clinical data from current or completed clinical trials or medical registries. In the practical part is described the implemented algorithm of detection, consists of several parts: import of data from information system, preprocessing and transformation of imported data records with variables of different data types into numerical vectors, using well known statistical methods for detection outliers and evaluation of the quality and accuracy of the algorithm. The result of creating the algorithm is vector of parameters containing anomalies, which has to make the work of data manager easier. This algorithm is designed for extension the palette of information system functions (CLADE-IS) on automatic monitoring the quality of data by detecting anomalous records.

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