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A modern approach to measuring antibiotic susceptibility of microbial cultures using machine learning
Lepík, Jakub ; Burget, Radim (referee) ; Čičatka, Michal (advisor)
The bachelor's thesis focuses on antibiotic susceptibility testing (AST), specifically enhancing and automating the assessment of the disk diffusion method using machine learning and object detection architectures. Thanks to the TensorFlow development platform and extensive dataset, on which custom detection models like EfficientDet were trained, processing a wide range of input data is enabled. This brings the possibility of using mobile devices alongside traditional laboratory equipment when evaluating this method. By employing additional image processing techniques and the OpenCV library, a custom algorithm for measuring the size of inhibitory zones was developed, which, along with the detection models, is integrated within the application module developed by Bruker Daltonics GmbH & Co. KG. This module, created using the ASP.NET platform, is a precise and valuable tool for assisting personnel in microbiological laboratories.
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Conversion of fingerprints captured by a mobile device into a standardized format - image editing
Mucha, Vojtěch ; Říha, Kamil (referee) ; Číka, Petr (advisor)
This bachelor thesis deals with the issue of fingerprint conversion taken by a mobile device into a standardized format. In the present day, mobile devices are used more and more often to acquire biometric data, fingerprints included. Processing and standardization of such data is an essential part of the subsequent biometric analysis. The aim of the work is to design and implement an algorithm which would convert a photo of a finger into a grey scale picture of its fingerprint with distinct papillary lines and subdued valleys. The algorithm is implemented in C++ using OpenCV library and a trained neural network for finger detection from hand image. The achieved results are evaluated according to the algorithms for assessing the quality of fingerprints NFIQ 2 and Innovatrics.
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Demonstration tasks of computer vision on a CNC milling machine
Duda, Pavel ; Honec, Peter (referee) ; Janáková, Ilona (advisor)
This bachelor thesis deals with the integration of computer vision into CNC machines in order to demonstrate the practical application of this technology. The task is to design several demonstration tasks to test and implement the various computer vision algorithms and subsequent data processing to control a CNC milling machine. In conclusion, we find an evaluation of the results and possible alternative steps to fulfill the problem.
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Optical and mechanical tracking of a moving object
Chaloupka, Radim ; Zemčík, Tomáš (referee) ; Honec, Peter (advisor)
The bachelor's thesis deals with the design of a pan-tilt platform with a camera, the design of controllers for its control, and the design and implementation of algorithms for the detection of predefined, moving objects. The task of the system is to find the object on the scene and maintain its position so that it is always in the center of the image sensor. The work uses the C++ programming language and Raspberry Pi hardware. PS and PSD controllers designed by the Ziegler-Nichols method are used for pan-tilt platform positioning, and interest point detection methods implemented in OpenCV libraries are used for optical tracing.
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Mobile Application for Scanning Nonograms and Solving It
Zobaník, Michal ; Pánek, Richard (referee) ; Dyk, Tomáš (advisor)
The goal of this bachelor thesis is to create mobile application for scanning nonograms from newspapers or magazines and allows its solving. The thesis describes the design of the application, its functionality and important parts of implementation. Image processing methods are used for detection of the nonogram. Number recognition is realized by created and trained convolutional network. Scanned nonograms are solved by using several logical rules and backtracking.
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Model Train Controlled by Computer
Černák, Filip ; Maršík, Lukáš (referee) ; Zemčík, Pavel (advisor)
The aim of this work was to simplify the automatic control of a model railway using a mobile device. The selected problem is solved using a program that scans the given railway. It detects model trains in the images and compares whether they are located in the areas marked by the user on them. If this occurs, the program will send a sequence of train and area specific commands to the specified command station. The created solution makes it possible to control switches and signals automatically, set the speed of locomotives in individual sections of the track and stop trains at stations. Furthermore, the solution will not allow two model trains to enter one section of the track. The benefit of this work is a simple way of automatically controlling a model railway for beginning modelers. The work gradually describes the concept of the solution, its subsequent implementation and the results of tests verifying the fulfillment of the assignment.
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Control and acquisition of data from camera sensor OV2312
Kováč, Dávid ; Kříž, Petr (referee) ; Přinosil, Jiří (advisor)
This bachelor thesis deals with the implementation of a driver for the camera sensor OV2312 into the libcamera framework, with the creation of an API interface that allows direct frame capture from a camera in the C++ language and with the creation of a program for demosaicing raw data from the camera sensor for the Raspberry Pi platforms. The aim of this thesis is not only the creation of software that would allow the camera sensor OV2312 to work with Raspberry Pi computers, but will also provide extended control options. The theoretical part describes the single board computers Raspberry Pi, the Libcamera library, the demosaicing process and the troubleshooting procedure. The output of the thesis is a modified Libcamera library that allows the user to capture images and change the parameters of the camera sensor. The created library for direct access to the camera in the C++ language allows to expand the capabilities of the camera sensor. The program for demosaicing provides the user the ability to convert raw data into images.
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Augmented Reality in Industrial Production and Maintenance
Kajan, Matej ; Janáková, Ilona (referee) ; Horák, Karel (advisor)
This paper seeks to explore the possibility to utilize XR (extended reality) in industrial assembly. The aim is to implement a system, which is able to visually navigate the operator during the product assembly process by the means of object recognition and image augmentation. The first chapter presents the use-case of augmented reality in the industry. The next part consists of research on the topic of augmented and virtual reality devices and provides a brief comparison of the current state of the art. Afterwards, a methodology is presented for object recognition of an arbitrary object. The implementation is able to detect the object in real-time, is resilient to occlusion and contains the information about the object’s orientation.
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Optimization of the positioning system of semiconductor chip testing
Kotian, Tomáš ; Jankovský, Jaroslav (referee) ; Otáhal, Alexandr (advisor)
The goal of this diploma thesis was to gather theoretical information on the possibilities of chip testing and subsequently design and apply necessary changes for the semi automatic positioning system, which would ensure its ability to test chips with the use of probe cards. Semi automatic positioning system is a result of a bachelor thesis, which ensured the ability of the machine to provide testing with the use of a resistance system created on a thick layer. The practical part of this thesis is focused on providing an accurate testing of the machine’s parametres and designing and applying necessary changes for the mechanical part of the machine. Furthermore, the thesis also describes the design and creation of an application with automatic detection of a chip, which is used for controlling the machine. The last part of the thesis describes the testing of the machine, which was realized with the use of two different sized chips.
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Drone position stabilization methods using image data
Koukal, Ondřej ; Raichl, Petr (referee) ; Janoušek, Jiří (advisor)
This bachelor’s thesis focuses on the design of an unmanned aircraft stabilization system. The purpose of this system is to determine the exact position of the unmanned aircraft in space based on image data from two cameras in real time. The theoretical part describes the image processing methods and the algorithm for determining the position of the unmanned aircraft. The practical part describes the implementation and testing of the system.
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