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Elliot Wave Detection
Kaleta, Marek ; Šperka, Svatopluk (referee) ; Petřík, Patrik (advisor)
This work deals with Elliott wave detection, which are statistical tool used to describe financial makret cycles and predict market trends. The work proposes methods to detect Elliott Waves and evaluetes them. From several methods of Elliott wave detection, Committee machines of multilayer perceptrons are used. Result of this work is a program, which detect Elliott impulse waves on input signal and builds hierarchy of Elliott waves.
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Estimation of Object Parameters from Images
Přibyl, Bronislav ; Hradiš, Michal (referee) ; Zemčík, Pavel (advisor)
Rapid expansion of communication technologies in last decade caused increased volume of information which is beeing generated and shared by people and organisations. It is permanently harder to identify relevant content today because of absence of tools and techniques which may support mass information management. As today's media have rather multimedial character image information is even more important. This project describes software for automatic estimation of predefined object parameters from images. A C++ implementation of this algorithm is also described.
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Improved Pattern Generation for Detection of Malicious Code
Štěpánek, Martin ; Regéciová, Dominika (referee) ; Křivka, Zbyněk (advisor)
This thesis deals with an automatic pattern generation, that can be used for detection of malicious code. The aim of this thesis is to create a tool to help the analysts to detect malware. Approaches of malware detection used in Avast Software are reviewed. A tool called YaraGen, which was improved in this work, is presented. New analyses implemented for YaraGen are introduced. The main contribution of this thesis are behavioral analyses of a malicious code.
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Handwritten Character Recognition Using Artificial Neural Networks
Smejkal, Vojtěch ; Fapšo, Michal (referee) ; Plchot, Oldřich (advisor)
Thesis deals with handwritten block letters and digits recognition using artificial neural networks. Text segmentation algorithms, feature extraction methods and backpropagation learning are explained. There are also described performed experiments with variety of configurations on datasets. Application with graphical user interface and interactive mouse-written text recognition was created to train new neural networks and test their effectivity.
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Barcode recognition system
Pribula, Wojciech ; Richter, Miloslav (referee) ; Petyovský, Petr (advisor)
This thesis describes barcodes which are used in postal services. Specifically, it is concerned with Intelligent Mail Barcode, the GS1-128 code, the C128 code of Ceska posta (Czech Postal Services) and the QR code. The thesis attempts to analyze methods of encoding information into barcodes and error detection algorithms used for error correction during the decoding processes. Most importantly, there is described Reed-Solomon error correction in the QR code. There are presented and evaluated different methods of code detecting which are suggested by authors of various academic articles. The thesis also describes the method of creating test sets of images and proposed appearances of the scanning scene. Additionally, there are described algorithms for detection and decoding barcodes GS1-128, C128 and IMB in the image which was created during the work on this thesis. Finally, there is the evaluation of the percentage success of algorithms.
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Pattern Recognition in Temporal Data
Hovanec, Stanislav ; Hynčica, Ondřej (referee) ; Honzík, Petr (advisor)
This diploma work initially conduct research in the area of descriptions and analysis of time series. The thesis then proceed to introduce the problems of technical analysis of price charts as well as indicators, price patterns and method of Pure Price Action. The method Pure Price Action is demonstrated in this work in two practical examples of its application to real businesses with a view to discovering and analyzing price patterns, as well as analysis and prediction of future price and financial evolution. This analysis is an introduction to the processes of successful business, following on from this we discuss the theme of Pattern Recognition and the Instance Based Learning method. The practical aspect of this work is carried out with the aid of a MATLAB applied algorithm for the analysis of the price pattern Correction for sale and purchase in dynamic time segments, specifically in trading price graphs, like those used for commodities or stock trading. For the analysis of time series we use the Pure Price Action method. The Instance Based Learning method is used by the algorithm to recognize price patterns. The created algorithm is verified on real data of a 5 minute time series of the US Dow Jones price charts for the years 2006, 2007, 2008. The achieved accuracy is evaluated with the aid of Equity Curves.
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System for Pattern Recognition in Binary Files
Milkovič, Marek ; Kolář, Dušan (referee) ; Matula, Peter (advisor)
Malicious software spreads really fast in the age of the Internet and it harms users and their data. Therefore, it is necessary to improve methods of how we deal with its analysis, so we can protect potential victims. This thesis deals with design and implementation of system for generating patterns out of executable files in cooperation with AVG Technologies. The goal of this work is to create a tool that generates a detection pattern from the set of binary files. This work further proposes new types of analyses for extraction of information out of executable files. Designed and implemented system is used in practice for analysis of new malicious code and it is integrated into the clustering system.
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Demonstrational Program for IZU Course
Hreha, Tomáš ; Šůstek, Martin (referee) ; Zbořil, František (advisor)
This bachelor thesis deals with the design of application for visualization of fundamental algorithms of artificial intelligence. The first part describes theoretical part of implemented topics and methods, next part briefly describes used technologies, reasons why they were used and their practical usage in context of result application. The next part is dedicated to user interface, its main components and describes ways how application interacts with user and how user can interact with application. The last part contains comparison with original demo applications and summarize results of application testing.
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Application of AdaBoost
Wrhel, Vladimír ; Šilhavá, Jana (referee) ; Hradiš, Michal (advisor)
Basics of classification and pattern recognitions will be mentioned in this work. We will focus mainly on AdaBoost algorithm, which serves to create a strong classifier function by some weak classifiers. We shall get acquainted with some modifications of AdaBoost. These modifications improve some of AdaBoost attributes. We shall also look into weak classifiers and features applicable to them. We shall especially look into the Haar- likes features. We shall discus possibilities of using the mentioned algorithms and features in facial expression recognition. We shall describe the situation between facial expression databases. We shall draw out a possible implementation of application of facial expression recognition.
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