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Automatic Photography Categorization
Veľas, Martin ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This thesis deals with content based automatic photo categorization. The aim of the work is to create an application, which is would be able to achieve sufficient precision and computation speed of categorization. Basic solution involves detection of interesting points, extraction of feature vectors, creation of visual codebook by clustering, using k-means algorithm and representing visual codebook by k-dimensional tree. Photography is represented by bag of words - histogram of presence of visual words in a particular photo. Support vector machines (SVM) was used in role of classifier. Afterwards the basic solution is enhanced by dividing picture into cells, which are processed separately, computing color correlograms for advanced image description, extraction of feature vectors in opponent color space and soft assignment of visual words to extracted feature vectors. The end of this thesis concerns to experiments of of above mentioned techniques and evaluation of the results of image categorization on their usage.
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Optical side channel
Kolofík, Josef ; Mačák, Jaromír (referee) ; Martinásek, Zdeněk (advisor)
This thesis deals with the optical side channel and using a neural network as classifier of data. The first part deals with the basics of cryptography and attacks on the cryptographic module. The second part deals with methods of decapsulation the microcontroller, decapsulation technological processes and methods of detection of photons. The third part deals with the use of neural networks as the basis of recognition and data classification software. In conclusion, the thesis describes the procedure for creating this software, analyzes the source code and tests the functionality of this solution.
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Exploitation of Graphics Processor as Accelerator - OpenCL Technology
Hrubý, Michal ; Jošth, Radovan (referee) ; Zemčík, Pavel (advisor)
This work deals with the OpenCL technology and its use for the task of object detection. The introduction is devoted to description of OpenCL fundamentals, as well as basic theory of object detection. Next chapter of the work is analysis, with design proposal which takes into consideration the possibilities of OpenCL. Further, there's description of implementation of detection application and experimental evaluation of detector's performance. The last chapter summarizes the achieved results.
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Decision Tree Design Based on Evolutionary Algorithms
Benda, Ondřej ; Trzos, Michal (referee) ; Karásek, Jan (advisor)
Tato diplomová práce pojednává o dvou algoritmech pro dolování z proudu dat - Very Fast Decision Tree (VFDT) a Concept-adapting Very Fast Decision Tree (CVFDT). Je vysvětlen princip klasifikace rozhodovacím stromem. Je popsána základní myšlenka konstrukce stromu Hoeffding Tree, který je základem pro algoritmy VFDT a CVFDT. Tyto algoritmy jsou poté rozebrány detailněji. Dále se tato práce zabývá návrhem algoritmu Genetického Programování (GP), který je použit pro vytváření klasifikátoru obrazových dat. Vytvořený klasifikátor je použit jako alternativní způsob klasifikace objektů v obraze ve frameworku Viola-Jones. V práci je rozebrána implementace algoritmů, které jsou implementovány v jazyce Java. Algoritmus GP je integrován do knihovny “Image Processing Extension” programu RapidMiner. Algoritmy VFDT a CVFDT jsou testovány na syntetických a reálných textových datech. Algoritmus GP je testován na klasifikaci obrazových dat a následně vytvořený klasifikátor je otestován na detekci obličejů v obraze.
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Movement Abnormalities Classification using Genetic Programming
Chudárek, Aleš ; Mrázek, Vojtěch (referee) ; Drahošová, Michaela (advisor)
When suppressing the symptoms of Parkinson's disease, the correct dosage of drugs is critical for the patient. Improper dosing can either cause insufficient suppression of symptoms or, conversely, side effects, such as dyskinesia, occur with high doses. Dyskinesia is manifested by involuntary muscle movement. This work deals with the automated classification of dyskinesia from motion data recorded using a triaxial accelerometer located on the patient's body. In this work, the classifier of dyskinesia is automatically designed using Cartesian genetic programming. The designed classifier achieves very good quality of classification of severe dyskinesia (AUC = 0,94), which is a comparable result to the techniques presented in scientific literature.
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Face recognition
Škrobák, Dalibor ; Číka, Petr (referee) ; Kyselý, František (advisor)
This thesis is focused on face detection in static picture. Theoretical part contains color spaces (RGB, HSI, YCbCr), methods for skin detection (explicit, parametric or non-parametric methods), image metric, edge detection, mathematical morphology, methods for classification faces (appearance-based methods, feature invariant approaches, knowledge-based methods, template matching methods). Practical part of this thesis contains concept and practical realization two algorithms for segmentation skin in static image (simple method based on Cr chroma components and statistical method). Practical part contains concept and practical realization two algorithms for classification face (appearance-based method and template matching method) too.
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Image Processing Algorithms Optimization Using C++ Templates
Čepl, Radek ; Vyskočil, Michal (referee) ; Španěl, Michal (advisor)
Bachelor's thesis deals with image processing algorithm AdaBoost optimalization using C++ templates. Head aim of this thesis is effective evaluation of Haar Features with constant size. It also compares speed of feature detection on classical and template evaluation. The computer programme was written in C++ programming language using OpenCV graphic library and TinyXML library. Application was created and tested under Windows XP operating system.
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Building Model Generator for Open Street Maps
Libosvár, Jakub ; Láník, Aleš (referee) ; Polok, Lukáš (advisor)
This thesis deals with the procedural generation of building models based on a given pattern. The community project OpenStreetMap is used for obtaining datasets that create the buildings platform patterns. A brief survey of classifiers and formal grammars for modeling is introduced. Designing an estate classifier and algorithm for building generation is practical aspect of this thesis, including the algorithm implementation. 3D output meshes are rendered using OpenGL in real-time.
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Object Detection on GPU
Macenauer, Pavel ; Polok, Lukáš (referee) ; Juránek, Roman (advisor)
This thesis addresses the topic of object detection on graphics processing units. As a part of it, a system for object detection using NVIDIA CUDA was designed and implemented, allowing for realtime video object detection and bulk processing. Its contribution is mainly to study the options of NVIDIA CUDA technology and current graphics processing units for object detection acceleration. Also parallel algorithms for object detection are discussed and suggested.
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Neural networks for EMC modeling of small airplanes
Koudelka, Vlastimil ; Goňa,, Stanislav (referee) ; Raida, Zbyněk (advisor)
This thesis deals with neural modeling of electromagnetic field inside small aircrafts, witch can contain composite materials in their construction. Introduction to neural networks and its application in EMC of small airplanes is discussed in the first part of the text. In the second part of this thesis we design a simple EM model of small airplane. The airplane is simulated by two parallel dielectric layers (the left-hand side wall and the right hand side wall of the airplane). The layers are put into a rectangular metallic waveguide terminated by the absorber in order to simulate the illumination of the airplane by the external wave (both of the harmonic nature and pulse one). Numerical analyses are performed to search the relations between the distribution of an electromagnetic field inside the aircraft and electric parameters of model walls. The results of numerical analyses are used to train two types of neural network. In this way we can obtain accurate continuous model of electromagnetic field inside the aircraft. For the comparison with neural networks a multi-dimensional cubic spline interpolation is provided also. Neural classifiers are also investigated. We use them for classification of imaginary composite materials in terms of EMC. The nearest neighbour algorithm is applied as a classic approach to problem of classification.
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