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Detection, Localization and Recognition of Traffic Signs
Svoboda, Tomáš ; Juránek, Roman (referee) ; Herout, Adam (advisor)
This master's thesis deals with the localization, detection and recognition of traffic signs. The possibilities of selection of areas with possible traffic signs occurrence are analysed. The properties of different kinds of features used for traffic signs recognition are described next. It focuses on the features based on histogram of oriented gradients. Some possible classifiers are discussed, in the first place the cascade of support vector machines, which are used in resulting system. A description of the system implementation and data sets for 5 types of traffic signs is part of this thesis. Many experiments were accomplished with created system. The results of the experiments are very good. New datasets were acquired from approximately 9 hours of processed video sequences. There are about 13 500 images in these datasets.
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Verification of Authenticity of Stamps in Documents
Micenková, Barbora ; Španěl, Michal (referee) ; Herout, Adam (advisor)
Klasická inkoustová razítka, která se používají k autorizaci dokumentů, se dnes díky rozšíření moderních technologií dají relativně snadno padělat metodou oskenování a vytištění. V rámci diplomové práce je vyvíjen automatický nástroj pro ověření pravosti razítek, který najde využití zejména v prostředích, kde je nutné zpracovávat velké množství dokumentů. Procesu ověření pravosti razítka musí přirozeně předcházet jeho detekce v dokumentu - úloha zpracování obrazu, která zatím nemá přesvědčivé řešení. V této diplomové práci je navržena zcela nová metoda detekce a ověření pravosti razítka v barevných obrazech dokumentů. Tato metoda zahrnuje plnou segmentaci stránky za účelem určení kandidátních řešení, dále extrakci příznaků a následnou klasifikaci kandidátů za pomoci algoritmu podpůrných vektorů (SVM). Evaluace ukázala, že algoritmus umožňuje rozlišovat razítka od jiných barevných objektů v dokumentu jako jsou například loga a barevné nápisy. Kromě toho algoritmus dokáže rozlišit pravá razítka od kopií.
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Creation of New Prediction Units in Data Mining System on NetBeans Platform
Havlíček, David ; Bartík, Vladimír (referee) ; Lukáš, Roman (advisor)
The issue of this master's thesis is a creation of new prediction unit for existing system of knowledge discovery in database. The first part of project deal with general problems of knowledge discovery in database and predictive analysis. The second part of the project deal with system developed on FIT, for which is module implemented, used technologies, concept and implementation of mining module for this system. The solution is implemented in Java language and is a built on the NetBeans platform.
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Intelligent Mailbox
Pohlídal, Antonín ; Drozd, Michal (referee) ; Chmelař, Petr (advisor)
This master's thesis deals with the use of text classification for sorting of incoming emails. First, there is described the Knowledge Discovery in Databases and there is also analyzed in detail the text classification with selected methods. Further, this thesis describes the email communication and SMTP, POP3 and IMAP protocols. The next part contains design of the system that classifies incoming emails and there are also described realated technologie ie Apache James Server, PostgreSQL and RapidMiner. Further, there is described the implementation of all necessary components. The last part contains an experiments with email server using Enron Dataset.
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Automatic Photography Categorization
Veľas, Martin ; Řezníček, Ivo (referee) ; Španěl, Michal (advisor)
This thesis deals with content based automatic photo categorization. The aim of the work is to experiment with advanced techniques of image represenatation and to create a classifier which is able to process large image dataset with sufficient accuracy and computation speed. A traditional solution based on using visual codebooks is enhanced by computing color features, soft assignment of visual words to extracted feature vectors, usage of image segmentation in process of visual codebook creation and dividing picture into cells. These cells are processed separately. Linear SVM classifier with explicit data embeding is used for its efficiency. Finally, results of experiments with above mentioned techniques of the image categorization are discussed.
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Learnable Evolution Model for Optimization (LEM)
Grunt, Pavel ; Vašíček, Zdeněk (referee) ; Schwarz, Josef (advisor)
My thesis is dealing with the Learnable Evolution Model (LEM), a new evolutionary method of optimization, which employs a classification algorithm. The optimization process is guided by a characteristics of differences between groups of high and low performance solutions in the population. In this thesis I introduce new variants of LEM using classification algorithm AdaBoost or SVM. The qualities of proposed LEM variants were validated in a series of experiments in static and dynamic enviroment. The results have shown that the metod has better results with smaller group sizes. When compared to the Estimation of Distribution Algorithm, the LEM variants achieve comparable or better values faster. However, the LEM variant which combined the AdaBoost approach with the SVM approach had the best overall performance.
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Voice Activity Detection
Ent, Petr ; Karafiát, Martin (referee) ; Matějka, Pavel (advisor)
Práce pojednává o využití support vector machines v detekci řečové aktivity. V první části jsou zkoumány různé druhy příznaků, jejich extrakce a zpracování a je nalezena jejich optimální kombinace, která podává nejlepší výsledky. Druhá část představuje samotný systém pro detekci řečové aktivity a ladění jeho parametrů. Nakonec jsou výsledky porovnány s dvěma dalšími systémy, založenými na odlišných principech. Pro testování a ladění byla použita ERT broadcast news databáze. Porovnání mezi systémy bylo pak provedeno na databázi z NIST06 Rich Test Evaluations.
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Road Sign Detection from Camera in Car
Dušek, Jan ; Sochor, Jakub (referee) ; Beran, Vítězslav (advisor)
This bachelor's thesis is focused on detection of traffic signs from image or video. Algorithms common for object detection will be introduced in the beginning. Description of object detection using histogram of oriented gradients and support vector machines will follow. Last part will present accomplished results.
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Automatic Content-Based Image Categorization
Němec, Ladislav ; Španěl, Michal (referee) ; Veľas, Martin (advisor)
This thesis deals with automatic content-based image classification. The main goal of this work is implementation of application which is able to perform this task automatically. The solution consists of variable system using local image features extraction and visual vocabulary built by k-means method. Bag Of Words representation is used as a global feature describing each image. Support Vector Machines - the final component of this system - perform the classification based on this representation. In the last chapter, the results of this experimental system are presented.
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Automatic Recognition of Logopaedic Defect in Speech Utterances
Dušil, Lubomír ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The thesis is aimed at an analysis and automatic detection of logopaedic defects in speech utterance. Its objective is to facilitate and accelerate the work of logopaedists and to increase percentage of detected logopaedic defects in children of the youngest possible age followed by the most successful treatment. It presents methods of speech work, classification of the defects within individual stages of child development and appropriate words for identification of the speech defects and their subsequent remedy. After that there are analyses of methods of calculating coefficients which reflect human speech best. Also classifiers which are used to discern and determine whether it is a speech defect or not. Classifiers exploit coefficients for their work. Coefficients and classifiers are being tested and their best combination is being looked for in order to achieve the highest possible success rate of the automatic detection of the speech defects. All the programming and testing jobs has been conducted in the Matlab programme.
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