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Interactive Searching in Online Archive of Visual and Audiovisual Artworks
Kuře, Dominik ; Myška, Vojtěch (referee) ; Schimmel, Jiří (advisor)
This bachelor thesis focuses on development of a web application, which serves as an archive for videos. Each video has a certain amount of keywords. The application uses an already created database and a preinstalled server on which the videos are uploaded. The database was given to the author by his supervisor. Searching through the archive can be done by inputting an expression into a search bar or through a variation of filters that are based on information about each video. The results and the database as a whole are graphically represented by charts, which change their form based on given data. Videos can be played in a video player and a list of similar videos is generated. The list is based on keywords which the videos have in common. The main technologies used in the application are Node.js, React and MariaDB. A good amount of libraries are used for this application, allowing JavaScript to be the primary programming language in all phases of development. The text of this bachelor thesis can be dividen in two parts - theoretical and practical. The first part describes all the technologies and libraries used in the application. An in depth approach was taken especially on those parts of each library which are actually being used in the practical. Apart from the necessary technologies, the reader will be also introduced to libraries and systems which help a programmer with his work such as automatic formatting of code and it's backup, saving different versions of the code or adding static datatypes into JavaScript through TypeScript. The theoretical part should give the reader a summary of how browser applications work and communicate with each other. In the practical part an entire application will be built from scratch. The application will connect four different servers - front-end, back-end, database server and a server storing the videos - and allow them to communicate accordingly. The bachelor thesis also contains information about using different controllers for manipulating the browser.
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Creation of Bluetooth data logger for recording and processing of measured data
Vaverka, Jan ; Myška, Vojtěch (referee) ; Dejdar, Petr (advisor)
The first part of the theses deals with dataloggers and their use in today's world. The second part is dedicated to microcontrollers which are used as a control unit for dataloggers. Individual peripheral devices MCU and their communication interfaces have been described. The next part deals with Bluetooth Low Energy which is used for data broadcasting to the user. Based on the acquired knowledge the microcontroller and sensors were selected. A datalogger was constructed and programmed from selected components, which will measure the properties of ferment during fruit fermentation. Finally, a mobile application was created to download data from the datalogger and then display the data in charts.
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Image segmentation using graph neural networks
Boszorád, Matej ; Kolařík, Martin (referee) ; Myška, Vojtěch (advisor)
This diploma thesis describes and implements the design of a graph neural network usedfor 2D segmentation of neural structure. The first chapter of the thesis briefly introduces the problem of segmentation. In this chapter, segmentation techniques are divided according to the principles of the methods they use. Each type of technique contains the essence of this category as well as a description of one representative. The second chapter of the diploma thesis explains graph neural networks (GNN for short). Here, the thesis divides graph neural networks in general and describes recurrent graph neural networks(RGNN for short) and graph autoencoders, that can be used for image segmentation, in more detail. The specific image segmentation solution is based on the message passing method in RGNN, which can replace convolution masks in convolutional neural networks.RGNN also provides a simpler multilayer perceptron topology. The second type of graph neural networks characterised in the thesis are graph autoencoders, which use various methods for better encoding of graph vertices into Euclidean space. The last part ofthe diploma thesis deals with the analysis of the problem, the proposal of its specific solution and the evaluation of results. The purpose of the practical part of the work was the implementation of GNN for image data segmentation. The advantage of using neural networks is the ability to solve different types of segmentation by changing training data. RGNN with messaging passing and node2vec were used as implementation GNNf or segmentation problem. RGNN training was performed on graphics cards provided bythe school and Google Colaboratory. Learning RGNN using node2vec was very memory intensive and therefore it was necessary to train on a processor with an operating memory larger than 12GB. As part of the RGNN optimization, learning was tested using various loss functions, changing topology and learning parameters. A tree structure method was developed to use node2vec to improve segmentation, but the results did not confirman improvement for a small number of iterations. The best outcomes of the practical implementation were evaluated by comparing the tested data with the convolutional neural network U-Net. It is possible to state comparable results to the U-Net network, but further testing is needed to compare these neural networks. The result of the thesisis the use of RGNN as a modern solution to the problem of image segmentation and providing a foundation for further research.
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Client-server search engine for optimal public transport routes
Brát, Daniel ; Hošek, Jiří (referee) ; Myška, Vojtěch (advisor)
This bachelor thesis deals with the design and implementation of a client-server based program for finding the optimal path in public transport networks. Theoretical basics describe the Traveling salesman problem and mention some methods for finding its solution. This chapter is followed by a theoretical design of the application itself. Next chapter describes chosen technologies to be used. The last chapter describes the realization of the application itself. Reached goals are described in the conclusion.
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Recurrent Neural Network for Text Classification
Myška, Vojtěch ; Kolařík, Martin (referee) ; Povoda, Lukáš (advisor)
Thesis deals with the proposal of the neural networks for classification of positive and negative texts. Development took place in the Python programming language. Design of deep neural network models was performed using the Keras high-level API and the TensorFlow numerical computation library. The computations were performed using GPU with support of the CUDA architecture. The final outcome of the thesis is linguistically independent neural network model for classifying texts at character level reaching up to 93,64% accuracy. Training and testing data were provided by multilingual and Yelp databases. The simulations were performed on 1200000 English, 12000 Czech, German and Spanish texts.
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Client-server password manager
Myška, Vojtěch ; Burda, Karel (referee) ; Ležák, Petr (advisor)
This bachelor thesis deals with implementation password manager with client-server architecture. Basis of thesis is proposal of graphical user interface, used keys, remote methods, server and its database, choise of used technology and programming language. The next part delas with implementation proposal of password manager.
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