National Repository of Grey Literature 110 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Detection of anomalies in data center network traffic
Korzhasbayeva, Leila ; Uher, Václav (referee) ; Burget, Radim (advisor)
Ve velkých společnostech existuje spousta kriticky důležitých strojů pracujících bez přestávky každý den. Jednoduché Log Management řešení není vždy dostatečné k zachycení všech dat, která tečou produkčním prostředí. Ani bezpečnostní analytik není vždy schopen sledovat každý zdroj v prostředí, chytat změny v běžném provozu. Zde je bod, kde nám stroj může pomoci. Detekce anomálií v prostředí je hlavním cílem tohoto projektu. Existuje několik řešení prezentovaných a testovaných na datech ze serverů v reálném prostředí definované společnosti. Některé false positives stále se mohou objevovat, ale je to dobrá příležitost k vyřešení v budoucím výzkumu.
Plug-in for Eclipse environment
Zaytsev, Vsevolod ; Burget, Radim (referee) ; Sysel, Petr (advisor)
This bachelor’s thesis has a goal to design a new DLTK-based (Dynamic Languages Toolkit) plug-in for the Eclipse development environment. Theoretical part of the thesis engages on the architecture of the Eclipse and describes the possibility of its extension through its own plug-ins, particularly for support of the Octave script language. Practical part of the thesis describes the creation of new plug-in for the Eclipse development environment, it’s integration and activation.
Enhancement of image quality for security forces
Varga, Adam ; Galáž, Zoltán (referee) ; Burget, Radim (advisor)
This bachelor thesis deals with image quality enhancement for security forces. Image quality enhancement in this case means increasing the resolution of image data by using super-resolution techniques using models of deep convolutional neural networks. The thesis in its theoretical part describes the principles of the operation of this technique and in its practical part is presented the work with selected state-of-the-art models in the area of super-resolution.
Predictive maintenance for automated assembly machines
Janík, Vladimír ; Burget, Radim (referee) ; Mecerod, Václav (advisor)
This thesis deals with data analysis. Data obtained from automated assembly machines and their quick and well-arranged displaying in a format suitable for individual end users. In the thesis web frameworks are compared and database structure as well as final software solution is proposed. The data is loaded using the implemented programming language module. The data is further analyzed and displayed to a user through a web-based application accessible to end user from every device connected to the corporate network.
People recognition using facial images
Lindovský, Michal ; Burget, Radim (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis focuses on the person recognition between several millions of people in a few seconds. As a part of my thesis is comparison of two programs which are used for recognizing faces - OpenFace and Face Recognition. Computing times of localization and face encoding are compared. The accuracy of recognition in various tests is compared as well, such as blurred image, brightness changes, age of person or usage of sunglasses. Created web application is made for recognizing people in different databases. Is possible to add or remove databases of people in the application. The application allows to subsume people into database by gender automatically or manually. Face recognition can be speeded up by using multiple processor cores.
Client Generator for Language Server Protocol
Jelínek, Dominik ; Burget, Radim (referee) ; Číka, Petr (advisor)
The Diploma thesis deals with the Microsoft Language Server Protocol. The theoretical part describes the architecture and protocol properties, the LSP implementation within the Eclipse and VS Code development environments and a procedure for creating a new plug-in in the Eclipse and VS Code. In addition, the theoretical part familiarizes with Apache Camel project and implementation of Camel Language server and Camel Language clients for extended language support. The last mention in the theory is about the Yeoman tool for scaffolding a new projects. The description of the practical part deals with properties and implementation of the created LSP clients generator for Language Server Protocol.
Application for geolocation databases
Klíma, Oldřich ; Burget, Radim (referee) ; Komosný, Dan (advisor)
The thesis deals with possibilities for more precise determination of geographical position of given IP address by combination of estimates of data obtained from geolocation databases. The first part introduces the issue on theoretical level. Possibilities of network device identification, its geographical location and principles of geolocation databases are described here. After analyzing the theoretical part of this issue, the current state of application for geolocation databases is described. The next section introduces a new application which uses original software ip2geotools as a library. Using the three implemented methods for combining results (based on average, median, and cluster analysis by K-Means algorithm), the new program allows to estimate the physical location of IP address. The app is complemented with console interface and geographic data visualization on the map. In the last part, the accuracy of computational methods is validated and a detailed statistical analysis of data obtained by performing a calculation over a set of IP addresses with known geographical location of the RIPE Atlas service is performed.
Deep neural network for supercomputer environments
Bronda, Samuel ; Kolařík, Martin (referee) ; Burget, Radim (advisor)
The main benefit of the work is the optimization of the hardware configuration for the calculation of neural networks. The theoretical part describes neural networks, deep learning frameworks and hardware options. The next part of the thesis deals with implementation of performance tests, which include application of Inception V3 and ResNet models. Network models are applied to various graphics cards and computing hardware. The output of the thesis is the implemented model of the network Inception V3, which examines the graphics cards and their performance, time-consuming calculations and their efficiency. The ResNet model is applied to a section that examines other impacts on neural network computing such as used disk, operating memory, and so on. Each practical part contains a discussion where the knowledge of the given part is explained. In the case of consumption measurement, a mismatch between the declaration by the manufacturer and the measured values was identified.
Neural network generator for image similarity measurement
Hipča, Tomáš ; Kolařík, Martin (referee) ; Burget, Radim (advisor)
This thesis deals with designing an automatic generator of deep neural networks for image classification. Theoretical part clarifies what a neural network and formal neuron are. Furthermore, the types of neural network architectures are presented. The focus of this thesis is convolutional neural networks, several pieces of research from this field are mentioned. The practical part of this thesis describes information with regards to the implementation of neural network generator, possible frameworks and programming languages for such implementation. Brief description of the implementation itself is presented as well as implemented layers. Generated neural networks are tested on Google-Landmarks dataset and results are commented upon.
Food classification using deep neural networks
Kuvik, Michal ; Přinosil, Jiří (referee) ; Burget, Radim (advisor)
The aim of this thesis is to study problems of deep convolutional neural networks and the connected classification of images and to experiment with the architecture of particular network with the aim to get the most accurate results on the selected dataset. The thesis is divided into two parts, the first part theoretically outlines the properties and structure of neural networks and briefly introduces selected networks. The second part deals with experiments with this network, such as the impact of data augmentation, batch size and the impact of dropout layers on the accuracy of the network. Subsequently, all results are compared and discussed with the best result achieved an accuracy of 86, 44% on test data.

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