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Advanced analysis of moving objects in transport
Hora, Adam ; Dejdar, Petr (referee) ; Kiac, Martin (advisor)
This thesis solves the problem of monitoring objects from live streams or camera recordings. The aim is also to create your own data set usable in solving traffic situations and analysis for object recognition and classification. The YOLO method with OpenCV support was used for evaluation purposes. The result is a program in which road recordings can be inserted or live broadcasts can be used from a camera positioned so that it captures the road. The output of the program is to find out the number of motor vehicles at any given moment and the average number of vehicles that were on the road during given periods of time. The videos from which the data set is created were provided by the thesis supervisor. The main benefit of this work is the ability to monitor traffic density at given time intervals.
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Monitoring of production facilities
Borsuk, Adam ; Kiac, Martin (referee) ; Číka, Petr (advisor)
The aim of the diploma thesis is to study the possibilities of creating a monitoring system for older production facilities already in operation. Select the necessary components for the nature of the equipment to create a system that is able to capture and provide information about activities on the equipment. The second goal is to design a suitable communication model for clear information about the operation, sending and storing data. The third goal is to analyze the dual-core ESP32 microprocessor against its predecessors in the role of system control unit.
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Advanced analysis of moving objects in the image
Medynskyi, Ivan ; Sikora, Pavel (referee) ; Kiac, Martin (advisor)
This work focuses on image processing using the OpenCV library and detecting moving objects in video using convolutional neural networks. The resulting application can detect moving objects in video or in real time and includes a user interface that allows the user to easily control the application. Part of this application is the YOLO convolutional model, which is designed to detect moving objects.
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Use of modern image processing methods in the control of laboratory processes
Kiac, Martin ; Říha, Kamil (referee) ; Krajsa, Ondřej (advisor)
The thesis deals with the processing and detection of specific objects in the image on the Android mobile platform. The main objective of this work was to design and then implement a mobile application for Android operating system, which allows control of pipetting processes based on images from a mobile device camera. The OpenCV library is used in the application for image processing. The resulting application should serve primarily in laboratories as a tool for complete analysis of the pipetting process. The work is divided into two main chapters, which further consist of sections and smaller subsections. The first chapter is devoted to the theoretical analysis of this work. Here is also describes used technology, Android operating system, OpenCV library and important parts of image processing. The second chapter deals with the proposal and subsequent practical solution of this work. There is a proposal and the following procedure for solving this work, important techniques, methods of processing and analysis of the camera image. The conclusion of the thesis is an evaluation of the results of the solution of this work.
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Detection of objects and tracking the route of movement of traffic participants for the needs of intelligent transport nodes
Vymazal, Tomáš ; Kiac, Martin (referee) ; Burget, Radim (advisor)
The master‘s thesis is focused on the object detection. The aim of this thesis is to desine an experiment to assess the detection models YOLOv5, YOLOR, Scaled-YOLOv4 and EfficientDet and to compare their properties (detection speed, memory requirements, accuracy and certainty of detection). For this purpose a custom data set is created to investigate these parameters. The study shows that the YOLOv5 network is performd as the best solution. Deep SORT is used for object tracking which is important for the subsequent extraction of training data from video footage for object movement prediction. The added value is the design of the prediction algorithm which is based on a polynomial regression model.
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A web interface for training neural networks
Szymutko, Jaromír ; Kiac, Martin (referee) ; Sikora, Pavel (advisor)
The thesis deals with the development of a web application for neural networks training. The introduction of the thesis outlines issues related to artificial intelligence and machine learning. Then the main tools used in the development of the application are described, including the Blazor and Keras.NET. The thesis describes the development process of a web application with a database that allows uploading datasets, creating a neural network model, training the model, and performing predictions on user-selected images. Finally, the resulting appearance and functionality of the application are presented.
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Advanced analysis of moving objects in transport
Hora, Adam ; Dejdar, Petr (referee) ; Kiac, Martin (advisor)
This thesis solves the problem of monitoring objects from live streams or camera recordings. The aim is also to create your own data set usable in solving traffic situations and analysis for object recognition and classification. The YOLO method with OpenCV support was used for evaluation purposes. The result is a program in which road recordings can be inserted or live broadcasts can be used from a camera positioned so that it captures the road. The output of the program is to find out the number of motor vehicles at any given moment and the average number of vehicles that were on the road during given periods of time. The videos from which the data set is created were provided by the thesis supervisor. The main benefit of this work is the ability to monitor traffic density at given time intervals.
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Real-time voice command recognition system
Šíbl, Evžen ; Kiac, Martin (referee) ; Přinosil, Jiří (advisor)
The bachelor thesis deals with the development of a system for voice command recognition. The classifier of this system was created using a neural network. In this thesis you will learn about the history and problems of speech recognition. A system has been created that detects a section in a recording containing a speech signal, which then uses the classifier to decide what word from the word table it is. Three models with the same architecture but with different training data were created. These models were then compared with each other. A simple user interface was created for the resulting system.
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Advanced image analysis using deep neural networks
Hynek, Vojtěch ; Přinosil, Jiří (referee) ; Kiac, Martin (advisor)
This bachelor thesis deals with the problem of object detection in images using a convolutional neural network. The result of this work is a custom dataset, a neural network model YOLOv4 and a script used to process the resulting model data. The dataset contains 8080 images on which 14 objects are annotated. The neural network model was reduced in depth, which significantly increased the speed of the detection itself. The script processing the resulting data calculates the 3D and GPS coordinates of the detected object in space. The paper concludes by summarizing the results of the model and at the same time suggesting how the quality of the dataset could be improved.
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Mobile application for an intelligent beekeeping system
Pecár, Martin ; Myška, Vojtěch (referee) ; Kiac, Martin (advisor)
The aim of this thesis is to design and create an application which will allow beekeepers to manage their hives with a mobile phone.The reason for this is centralisation and clarification of all colected data from visits to the hive, where this data could be later used to create statistics.Furthermore, this app contains ways to notify the beekeeper that there is a need of intervention with the hive using their own alerts and statistics of selected properties of a hive. The result of this work is the previously described application.
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