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Human Activity Recognition Using Smartphone
Novák, Andrej ; Červenák, Rastislav (referee) ; Burget, Radim (advisor)
The increase of mobile smartphones continues to grow and with it the demand for automation and use of the most offered aspects of the phone, whether in medicine (health care and surveillance) or in user applications (automatic recognition of position, etc.). As part of this work has been created the designs and implementation of the system for the recognition of human activity on the basis of data processing from sensors of smartphones, along with the determination of the optimal parameters, recovery success rate and comparison of individual evaluation. Other benefits include a draft format and displaying numerous training set consisting of real contributions and their manual evaluation. In addition to the main benefits, the software tool was created to allow the validation of the elements of the training set and acquisition of features from this set and software, that is able with the help of deep learning to train models and then test them.
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Use of Data Mining in Company Processes
Měchura, Dalibor ; Kříž, Jiří (referee) ; Luhan, Jan (advisor)
This masters thesis focuses on data mining techniques and business intelligence analysis. In accordance with the analysis of the current situation in the company, a complementary solution to the problem is proposed and a view of the existing data is provided from a different perspective, namely using RapidMiner. The output of the thesis is thus concrete analytical outputs for decision support in the company.
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Utilization of artificial intelligence in vibrodiagnostics
Dočekalová, Petra ; Huzlík, Rostislav (referee) ; Zuth, Daniel (advisor)
The diploma thesis deals with machine learning, expert systems, fuzzy logic, genetic algorithms, neural networks and chaos theory, which fall into the category of artificial intelligence. The aim of this work is to describe and implement three different classification methods, according to which the data set will be processed. The GNU Octave software environment was chosen for the data application for licensing reasons. Further evaluate the success of data classification, including visualization. Three different classification methods are used for comparison, so that we can compare the processed data with each other.
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Handwritten text recognition using a sliding window
Ďuriš, Denis ; Povoda, Lukáš (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis deals with optical character recognition. It focuses on recognizing hand-written text. The theoretical introduction describes the methods used for optical character recognition and selected machine learning methods. Subsequently, the work describes two methods for making cutouts of characters, using a sliding window. Cutouts are used in training and testing datasets of machine learning models. The document includes methods to improve the accuracy of character recognition. The accuracy of the models is evaluated in conclusion. Charcters in cutouts are clasified by an automated recognition program.
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Semantic Recognition of Comments on the Web
Stříteský, Radek ; Harár, Pavol (referee) ; Povoda, Lukáš (advisor)
The main goal of this paper is the identification of comments on internet websites. The theoretical part is focused on artificial intelligence, mainly classifiers are described there. The practical part deals with creation of training database, which is formed by using generators of features. A generated feature might be for example a title of the HTML element where the comment is. The training database is created by input of classifiers. The result of this paper is testing classifiers in the RapidMiner program.
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System for Detection of APT Attacks
Hujňák, Ondřej ; Kačic, Matej (referee) ; Barabas, Maroš (advisor)
The thesis investigates APT attacks, which are professional targeted attacks that are characterised by long-term duration and use of advanced techniques. The thesis summarises current knowledge about APT attacks and suggests seven symptoms that can be used to check, whether an organization is under an APT attack. Thesis suggests a system for detection of APT attacks based on interaction of those symptoms. This system is elaborated further for detection of attacks in computer networks, where it uses user behaviour modelling for anomaly detection. The detector uses k-nearest neighbors (k-NN) method. The APT attack recognition ability in network environment is verified by implementing and testing this detector.
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System for speaker diarization
Bradáč, Josef ; Atassi, Hicham (referee) ; Míča, Ivan (advisor)
Speaker diarization system has wide application in the field of processing and analysis speech signals. This work is broken down to introduction and follow for designing the system. Result of this work is an implementation of the system itself and its evaluation based on interview´s database.
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Human Activity Recognition Using Smartphone
Novák, Andrej ; Červenák, Rastislav (referee) ; Burget, Radim (advisor)
The increase of mobile smartphones continues to grow and with it the demand for automation and use of the most offered aspects of the phone, whether in medicine (health care and surveillance) or in user applications (automatic recognition of position, etc.). As part of this work has been created the designs and implementation of the system for the recognition of human activity on the basis of data processing from sensors of smartphones, along with the determination of the optimal parameters, recovery success rate and comparison of individual evaluation. Other benefits include a draft format and displaying numerous training set consisting of real contributions and their manual evaluation. In addition to the main benefits, the software tool was created to allow the validation of the elements of the training set and acquisition of features from this set and software, that is able with the help of deep learning to train models and then test them.
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LPR Recognition
Trkal, Ondřej ; Richter, Miloslav (referee) ; Horák, Karel (advisor)
The thesis deals with analysis and design of system for automatic localization and recognition of the license plate. The input images are from different sources, and contain large scenic and weather variations. The aim was to create a system able to find the licence plate on the image and recognize its alphanumeric figure. In this work, there is a focus on analysis and implementation of localization and optical character recognition methods. One own and four other localization methods are compared. There are also compared three classifiers for optical character recognition. Localization and OCR methods are tested on real data and evaluated in accordance with the calculated evaluation parameters. The work also contains sensitivity analysis of the proposed system.
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