|
|
A convolutional neural network for image segmentation
Mitrenga, Michal ; Petyovský, Petr (referee) ; Jirsík, Václav (advisor)
The aim of the bachelor thesis is to learn more about the problem of convolutional neural networks and to realize image segmentation. This theme includes the field of computer vision, which is used in systems of artificial intelligence. Special Attention is paid to the image segmentation process. Furthermore, the thesis deals with the basic principles of artificial neural networks, the structure of convolutional neural networks and especially with the description of individual semantic segmentation architectures. The chosen SegNet architecture is used in a practical application along with a pre-learned network. Part of the work is a database of CamVid images, which is used for training. For testing, a custom image database is created. Practical part is focused on CNN training and searching for unsuitable parameters for network learning using SW Matlab.
|
|
|
Development of KNX installation demo-board
Mitrenga, Michal ; KNX), Josef Kunc (Národní asociace (referee) ; Fiedler, Petr (advisor)
The aim of this diploma thesis is to compile a demonstration panel as an example of the functions of intelligent electrical installation KNX. One of the advantages of this system bus is the ability to use devices from multiple manufacturers. A total of 20 devices from 12 different manufacturers are used in this work. The work begins with an explanation of the principle on which the KNX system bus works, followed by a description of the equipment used and the electrical connection of the switchboard according to the wiring diagram. Next, how the whole panel was revived is described. The next chapter contains a detailed description of device programming in ETS, ie setting parameters for individual devices and assigning group addresses. The last chapter deals with visualization and remote control. It explains how a communication channel was created to connect the panel to a server from FlowBox. Using the web interface on this server, a visualization was created, which can be used to remotely control the entire panel from anywhere.
|
|
|
A convolutional neural network for image segmentation
Mitrenga, Michal ; Petyovský, Petr (referee) ; Jirsík, Václav (advisor)
The aim of the bachelor thesis is to learn more about the problem of convolutional neural networks for image segmentation. This theme encompasses the whole field of computer vision. Particular attention is paid to the image segmentation process. Furthermore, the thesis deals with the basic principles of artificial neural networks, the structure of convolutional neural networks and especially with the description of individual semantic segmentation architectures. Part of the thesis is an example of practical applications of image segmentation. An important part is the SYNTHIA database of images, where its properties are shown. At the end of the thesis, the terms and requirements for hardware performance and software needed for good network performance are described in more detail. The Keras framework has already been used, which already includes functions for working with neural networks.
|
|
|
Development of KNX installation demo-board
Mitrenga, Michal ; KNX), Josef Kunc (Národní asociace (referee) ; Fiedler, Petr (advisor)
The aim of this diploma thesis is to compile a demonstration panel as an example of the functions of intelligent electrical installation KNX. One of the advantages of this system bus is the ability to use devices from multiple manufacturers. A total of 20 devices from 12 different manufacturers are used in this work. The work begins with an explanation of the principle on which the KNX system bus works, followed by a description of the equipment used and the electrical connection of the switchboard according to the wiring diagram. Next, how the whole panel was revived is described. The next chapter contains a detailed description of device programming in ETS, ie setting parameters for individual devices and assigning group addresses. The last chapter deals with visualization and remote control. It explains how a communication channel was created to connect the panel to a server from FlowBox. Using the web interface on this server, a visualization was created, which can be used to remotely control the entire panel from anywhere.
|
|
|
A convolutional neural network for image segmentation
Mitrenga, Michal ; Petyovský, Petr (referee) ; Jirsík, Václav (advisor)
The aim of the bachelor thesis is to learn more about the problem of convolutional neural networks and to realize image segmentation. This theme includes the field of computer vision, which is used in systems of artificial intelligence. Special Attention is paid to the image segmentation process. Furthermore, the thesis deals with the basic principles of artificial neural networks, the structure of convolutional neural networks and especially with the description of individual semantic segmentation architectures. The chosen SegNet architecture is used in a practical application along with a pre-learned network. Part of the work is a database of CamVid images, which is used for training. For testing, a custom image database is created. Practical part is focused on CNN training and searching for unsuitable parameters for network learning using SW Matlab.
|
|
|
A convolutional neural network for image segmentation
Mitrenga, Michal ; Petyovský, Petr (referee) ; Jirsík, Václav (advisor)
The aim of the bachelor thesis is to learn more about the problem of convolutional neural networks for image segmentation. This theme encompasses the whole field of computer vision. Particular attention is paid to the image segmentation process. Furthermore, the thesis deals with the basic principles of artificial neural networks, the structure of convolutional neural networks and especially with the description of individual semantic segmentation architectures. Part of the thesis is an example of practical applications of image segmentation. An important part is the SYNTHIA database of images, where its properties are shown. At the end of the thesis, the terms and requirements for hardware performance and software needed for good network performance are described in more detail. The Keras framework has already been used, which already includes functions for working with neural networks.
|
guest ::
