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Analyzing a person’s handwriting for recognizing his/her emotional state
Chudárek, Aleš ; Matoušek, Jiří (referee) ; Malik, Aamir Saeed (advisor)
Rozpoznávání emocí z rukopisu je náročný a interdisciplinární úkol, který může poskytnout vhled do psychologického a emočního stavu pisatele. V této diplomové práci byl vyvinut a vyhodnocen model strojového učení schopný predikovat emoční stav pisatele na základě vzorků jeho rukopisu. Byl využit dataset EMOTHAW, který obsahuje vzorky rukopisu a kreseb od subjektů, jejichž emoční stavy byly změřeny pomocí testu DASS, který hodnotí úroveň deprese, úzkosti a stresu, a CIU Handwritten databázi pro ověření a experimentování. Bylo extrahováno množství příznaků inspirovaných standardní grafologií, stejně jako příznaky specifické pro online data. Pomocí ANOVA byly vybrány statisticky významné příznaky, které byly normalizovány pomocí Z-Score, MinMax, IQR nebo logaritmické transformace. Dimenzionalita příznaků byla snížena pomocí analýzy hlavních komponent (PCA) a lineární diskriminační analýzy (LDA). Pro klasifikaci byl použit meta-přístup Ensemble learning, který se snaží snížit chyby jednoho jednoduchého modelu využitím rozmanitosti a doplňkovosti více modelů. Struktura klasifikátoru závisí na mnoha argumentech, což vede k více než 300 000 různým konfiguracím. Optimální argumenty a tudíž optimální struktura byla hledána pomocí zamrazování argumentů. Byly identifikovány nejlepší klasifikátory pro binární a trinární klasifikaci každé emoce, což vedlo k šesti optimálním modelům. Tyto modely byly hodnoceny pomocí různých metrik, jako jsou accuracy, precision, recall a F1 Skóre, a dosáhly adekvátních výsledků ve všech metrikách. Kromě nalezení klasifikátorů tato práce zkoumala význam každého extrahovaného příznaku, čímž byl vytvořen seznam nejvýznamnějších příznaků použitých pro rozpoznávání emocí z rukopisu. Dále tato práce rozšiřuje databázi EMOTHAW identifikací úkolů, které jsou více indikativní pro specifické emoce, čímž se snižuje potřeba kompletní baterie úkolů pro emoční analýzu.
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Battery waste recycling
Song, Jiyul ; Brummer, Vladimír (referee) ; Jecha, David (advisor)
The bachelor's thesis focuses on methods for recycling batteries and rechargeable batteries. The thesis aimed to describe the possibilities for recycling battery waste and to conduct an experimental study on the drying of battery waste. The research included a review of the history, principles, and classification of batteries and accumulators, which are described in the theoretical section. Additionally, the thesis examined EU and Czech Republic legislation regarding electronic waste recycling. Finally, a practical experiment was conducted, focus-ing on the drying process of battery waste.
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Scene Analysis Based on the 2D Images
Hejtmánek, Martin ; Drahanský, Martin (referee) ; Orság, Filip (advisor)
This thesis deals with an object surface analysis in a simple scene represented by two-dimensional raster image. It summarizes the most common methods used within this branch of information technology and explains both their advantages and drawbacks. It introduces the design of an surface profile analysis algorithm based on the lighting analysis using knowledge and experiences from previous work. It contains a detailed description of the implemented algorithm and discusses the experimental results. It also brings up options for the possible enhancement of the projected algorithm.
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Preprocessing and Transformation of Text Data Collections
Maruna, Viktor ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This bachelor thesis deals with the issue of text-mining, mostly focused on preprocessing and transformation. In theoretical part there are contained information about development and principles of text-mining processes, text data collections and use in practice. The next part of this thesis describes in detail single steps of preprocessing and transformation of text data collections. In the final parts there are reviews of application development, testing and personal view on this thesis.
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Processing and Visualization of Mass Spectrums
Beneš, Ondřej ; Bendl, Jaroslav (referee) ; Martínek, Tomáš (advisor)
One of new techniques in the field of analytical chemistry, which has more and more practical use, is mass spectrometry imaging. With its ability to record representation of substances in samples during the tissue analyze arise problem with a lot of output data which needs to be handled programmatically. The goal of this work is to create an software for processing and visualization data of new standard imzML. As a part of the work, the field of mass spectrometry, primarily MALDI TOF mass spectrometry, is briefly introduced. There are also introduced some methods for mass spectrometry data preprocessing. The work also contains a summary of current state of available software for processing and visualization of mass spectrometry data. With requests from cooperating laboratory a novel software is designed and implemented, which besides the visualization itself, can preprocess the data for example data smoothing with Savitzky-Golay method, internal calibration or peak detection with continuous wavelet transformation. The software was successfully tested on real data sets.
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Neural Networks Classifier Design using Genetic Algorithm
Tomášek, Michal ; Vašíček, Zdeněk (referee) ; Mrázek, Vojtěch (advisor)
The aim of this work is the genetic design of neural networks, which are able to classify within various classification tasks. In order to create these neural networks, algorithm called NeuroEvolution of Augmenting Topologies (also known as NEAT) is used. Also the idea of preprocessing, which is included in implemented result, is proposed. The goal of preprocessing is to reduce the computational requirements for processing of benchmark datasets for classification accuracy. The result of this work is a set of experiments conducted over a data set for cancer cells detection and a database of handwritten digits MNIST. Classifiers generated for the cancer cells exhibits over 99 % accuracy and in experiment MNIST reduces computational requirements more than 10 % with bringing negligible error of size 0.17 %.
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Face detection and recognition with use of Raspberry Pi
Rozhoňová, Andrea ; Mézl, Martin (referee) ; Hesko, Branislav (advisor)
The following bachelor thesis is focused on the face detection and recognition in an image. The theoretical part divides methods of detection and recognition into several groups and there is better description and explanation of these methods in this part. At the end of the theoretical part is summarized the current utilization of person recognition on the bases of its face in practice. In the practical part is first implemented method for face detection. It is combination of two approaches - approach using haar features and approach using templates of eye. The face recognition is provided by the convolutional neural network. In conclusion there are summarized principles and problems associated with implementation on microcomputer Raspberry Pi and there is also evaluated the success of implemented methods.
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Realization of fingerprint scanner
Kovář, Martin ; Sekora, Jiří (referee) ; Mézl, Martin (advisor)
This master’s thesis deals with the issue of scanning human fingerprints, which is currently very topical and represents the most widespread biometric technology. The theoretical part of the work acquaints the reader with basics of dactyloscopy and biometrics and concerns technologies used for fingerprinting, image preprocessing methods and commercially available contactless optical scanners. The practical part is a realisation of a contactless optical scanner based on a Raspberry Pi minicomputer, implementation of preprocessing algorithms in Python and testing of the device from the perspective of image quality.
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Fast Visualization of Precise Shadows Using Precomputed Scene Geometry
Mikeš, Tibor ; Milet, Tomáš (referee) ; Pečiva, Jan (advisor)
The aim of this bachelor's thesis is to design and implement an effective method of rendering per-pixel correct hard shadows in scenes with static geometry. The principle of the method is in separate rendering of shadowed and lit surfaces. Whether a triangle is in shadow or not is known prior to its rasterization, which allows the renderer to omit per-fragment shadow calculations. Rendering a scene in this way requires it to be preprocessed. Therefore, two possible ways of preprocessing the scenes are described and implemented as well.
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Image-Based Licence Plate Recognition
Vacek, Michal ; Hradiš, Michal (referee) ; Beran, Vítězslav (advisor)
In first part thesis contains known methods of license plate detection. Preprocessing-based methods, AdaBoost-based methods and extremal region detection methods are described.Finally, there is a described and implemented own access using local detectors to creating visual vocabulary, which is used to plate recognition. All measurements are summarized on the end.
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