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Content Based Photo Search
Bařinka, Radek ; Přibyl, Bronislav (referee) ; Španěl, Michal (advisor)
This thesis deals with the problematics of searching of photographs by the content and existing applications dealing with this subject. The aim is the local working application for searching of photographs by the content given by a pattern. The solution consists of the simple graphical interface, the support of saving data and the reading of data from the transferable local database. The application searches the photographs of a given set that are similar to the given pattern. The results are visually depicted to the user. Feature extraction and detection by photo content is solved by means SURF algorithm, visual vocabulary created by method k-means and a description of photography as a bag of words. In addition,the searching of photographs by cosine similarity of vectors enriched with the independent calculation of homography and the selection of regions searched in an example photography. At the end of the technical report the results of testing are presented.
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Speech segmentation
Andrla, Petr ; Míča, Ivan (referee) ; Sysel, Petr (advisor)
The programme for the segmentation of a speech into fonems was created as a part of the master´s thesis. This programme was made in the programme Matlab and consists of several scripts. The programme serves for automatic segmentation. Speech segmentation is the process of identifying the boundaries between phonemes in spoken natural languages. Automatic segmentation is based on vector quantization. In the first step of algorithm, feature extraction is realized. Then speech segments are assigned to calculated centroids. Position where centroid is changed is marked as a boundary of phoneme. The audiorecords were elaborated by the programme and a operation of the automatic segmentation was analysed. A detailed manual was created to the programme too. Individual used methods of the elaboration of a speech were in the master´s thesis briefly descripted, its implementations in the programme and reasons of set of its parameters.
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Short-Term Forecast Based on Image of Sky
Volf, Martin ; Španěl, Michal (referee) ; Hradiš, Michal (advisor)
The bachelor's thesis submitted is dedicated to weather forecast based only on a video stream. At first, basic weather information which the sky can provide are presented. Cloud types including their properties and methods which the sky can most efficiently describe are dealt with. At second, basic circumstances between weather information are discussed. The objective of this work is to prove accuracy of the methods used for gaining data from the video stream and to find out whether it could be possible to use them for forecasting the rain, air humidity and sunshine for the period of time one hour later.
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Neural Network Based Image Segmentation
Jamborová, Soňa ; Řezníček, Ivo (referee) ; Žák, Pavel (advisor)
This work is about suggestion of the software for neural network based image segmentation. It defines basic terms for this topics. It is focusing mainly at preperation imaging information for image segmentation using neural network. It describes and compares different aproaches for image segmentation.
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Use of filter algorithms in cluster analysis
Pacovský, Matěj ; Antoch, Jaromír (advisor) ; Novák, Petr (referee)
The thesis is divided into five chapters. In the first two chapters I give the overview of clustering data analysis, I present definitions of terms used in the work and describe the k-means algorithm. Third chapter focuses on the filtering algorithm that uses heuristics when algorithm pass throught the MRKD-tree. The fourth chapter describes the x-means algorithm that uses all of the above-mentioned findings. In the fifth chapter I test all algorithms both on artificial and real data from physics. In some cases I refer to the WEKA program where the x-means algorithm is implemented. Algoritms that are discussed in this thesis are intended only for objects described by quantitative variables. They are also suitable for large datasets. In the attached CD I present the implementation of algorithms in Matlab language.
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RBF-networks with a dynamic architecture
Jakubík, Miroslav ; Mrázová, Iveta (advisor) ; Kukačka, Marek (referee)
In this master thesis I recapitulated several methods for data clustering. Two well known clustering algorithms, concretely K-means algorithm and Fuzzy C-means (FCM) algorithm, were described in the submitted work. I presented several methods, which could help estimate the optimal number of clusters. Further, I described Kohonen maps and two models of Kohonen's maps with dynamically changing structure, namely Kohonen map with growing grid and the model of growing neural gas. At last I described quite new model of radial basis function neural networks. I presented several learning algorithms for this model of neural networks, RAN, RANKEF, MRAN, EMRAN and GAP. In the end of this work I made some clustering experiments with real data. This data describes the international trade among states of the whole world.
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Use of filter algorithms in cluster analysis
Pacovský, Matěj ; Antoch, Jaromír (advisor) ; Novák, Petr (referee)
The thesis is divided into five chapters. In the first two chapters I give the overview of clustering data analysis, I present definitions of terms used in the work and describe the k-means algorithm. Third chapter focuses on the filtering algorithm that uses heuristics when algorithm pass throught the MRKD-tree. The fourth chapter describes the x-means algorithm that uses all of the above-mentioned findings. In the fifth chapter I test all algorithms both on artificial and real data from physics. In some cases I refer to the WEKA program where the x-means algorithm is implemented. Algoritms that are discussed in this thesis are intended only for objects described by quantitative variables. They are also suitable for large datasets. In the attached CD I present the implementation of algorithms in Matlab language.
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RBF-networks with a dynamic architecture
Jakubík, Miroslav ; Mrázová, Iveta (advisor) ; Kukačka, Marek (referee)
In this master thesis I recapitulated several methods for data clustering. Two well known clustering algorithms, concretely K-means algorithm and Fuzzy C-means (FCM) algorithm, were described in the submitted work. I presented several methods, which could help estimate the optimal number of clusters. Further, I described Kohonen maps and two models of Kohonen's maps with dynamically changing structure, namely Kohonen map with growing grid and the model of growing neural gas. At last I described quite new model of radial basis function neural networks. I presented several learning algorithms for this model of neural networks, RAN, RANKEF, MRAN, EMRAN and GAP. In the end of this work I made some clustering experiments with real data. This data describes the international trade among states of the whole world.
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RBF-networks with a dynamic architecture
Jakubík, Miroslav ; Mrázová, Iveta (advisor) ; Kukačka, Marek (referee)
In this master thesis I recapitulated several methods for clustering input data. Two well known clustering algorithms, concretely K-means algorithm and Fuzzy C-means (FCM) algorithm, were described in the submitted work. I presented several methods, which could help estimate the optimal number of clusters. Further, I described Kohonen maps and two models of Kohonen's maps with dynamically changing structure, namely Kohonen map with growing grid and the model of growing neural gas. At last I described quite new model of radial basis function neural networks. I presented several learning algorithms for this model of neural networks. In the end of this work I made some clustering experiments with real data. This data describes the international trade among states of the whole world.
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Content Based Photo Search
Bařinka, Radek ; Přibyl, Bronislav (referee) ; Španěl, Michal (advisor)
This thesis deals with the problematics of searching of photographs by the content and existing applications dealing with this subject. The aim is the local working application for searching of photographs by the content given by a pattern. The solution consists of the simple graphical interface, the support of saving data and the reading of data from the transferable local database. The application searches the photographs of a given set that are similar to the given pattern. The results are visually depicted to the user. Feature extraction and detection by photo content is solved by means SURF algorithm, visual vocabulary created by method k-means and a description of photography as a bag of words. In addition,the searching of photographs by cosine similarity of vectors enriched with the independent calculation of homography and the selection of regions searched in an example photography. At the end of the technical report the results of testing are presented.
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