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Web and Mobile App for Assigning and Confirming Tasks
Jeřábek, Filip ; Špaňhel, Jakub (referee) ; Herout, Adam (advisor)
This work solves managing employees by a dispatcher. The goal is to increase the efficiency of the work of a dispatcher, as well as a single employee's tasks. I focused on assigning tasks, event notification, and tasks state changes and all that in real-time. The solution consists of a website application that is used by a dispatcher and mobile application for employees. Website application is made in the PHP framework Symfony and the mobile app is made in the Flutter framework. The whole idea is to simplify the communication process. The dispatcher is able to check the state of assigned tasks whenever he needs, as well as the employee is notified about the newly assigned task, or changed task state, immediately. The solution significantly simplified the dispatcher's job. The idle times and unnecessary employee journeys were eliminated thanks to the immediate response, which made the whole process more effective. Following these facts, the overall costs should be lowered, and also more work should be made in the same amount of time.
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Counting Vehicles in Image and Video
Gabzdyl, Dominik ; Herout, Adam (referee) ; Špaňhel, Jakub (advisor)
Analýza silničního provozu je stále náročnou úlohou. V průběhu této úlohy se vyskytují mnohá úskalí, která je třeba brát na vědomí. Například malé rozlišení obrazu, vysoký počet překrývajících se objektů, úhel kamery, rozmazání objektů v důsledku jejich pohybu nebo povětrnostní podmínky. Tato práce adresuje tato úskalí použitím konvolučních neuronových sítí. V této práci představuji novou architektu založenou na principu počítání regresí (Counting by Regression). Navržená architektura je inspirována některými state-of-the-art architekturami a vylepšuje přesnost na různých datasetech. Například na velmi malém PUCPR+ datasetu byla odmocnina ze střední kvadratické chyby (RMSE) snížena z 34.46 na 6.99 vozidel (měřeno na test setu). Dosažené výsledky ukázaly, že je zde stále prostor ke zlepšení a možný další výzkum v oblasti počítání regresí.
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Detection of Traffic Signs and Lights
Oškera, Jan ; Špaňhel, Jakub (referee) ; Herout, Adam (advisor)
The thesis focuses on modern methods of traffic sign detection and traffic lights detection directly in traffic and with use of back analysis. The main subject is convolutional neural networks (CNN). The solution is using convolutional neural networks of YOLO type. The main goal of this thesis is to achieve the greatest possible optimization of speed and accuracy of models. Examines suitable datasets. A number of datasets are used for training and testing. These are composed of real and synthetic data sets. For training and testing, the data were preprocessed using the Yolo mark tool. The training of the model was carried out at a computer center belonging to the virtual organization MetaCentrum VO. Due to the quantifiable evaluation of the detector quality, a program was created statistically and graphically showing its success with use of ROC curve and evaluation protocol COCO. In this thesis I created a model that achieved a success average rate of up to 81 %. The thesis shows the best choice of threshold across versions, sizes and IoU. Extension for mobile phones in TensorFlow Lite and Flutter have also been created.
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Vehicle On-Board Camera Analysis
Kadeřábek, Jan ; Bartl, Vojtěch (referee) ; Špaňhel, Jakub (advisor)
This thesis focuses on analysis of video from vehicle on-board camera. During the process of analysis, probihibitory traffic signs are detected and their specific type is classified. For recognized speed limit signs, their numeric value is extracted. From the processed information, it will try to create a file containing the unique occurrences of traffic signs including their GPS coordinates. For the purpose of detection and recognition of traffic signs, several data sets were created. A~cascade classifier with LBP features is used as a detector. Classification of the type and value of traffic signs is done using the k-Nearest Neigbour method.
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Virtual Tour of FIT for Oculus Quest
Janů, Michal ; Špaňhel, Jakub (referee) ; Herout, Adam (advisor)
The main goal of this work is to make an application for VR headset Oculus Quest. This application has several features that allow the user to do more than just walk freely around the FIT BUT areal, such as Navigation, Instant travel, and viewing basic room information. The Navigation feature is used to find the shortest route to the desired office or lecture room, where every room has its panel with information about the room. The instant travel feature allowes choosing a starting location.
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Web Application for Simple Management of Deadlines
Šmajzrová, Kateřina ; Špaňhel, Jakub (referee) ; Herout, Adam (advisor)
This work solves the creation of a simple web application that allows one administrator to easily manage his tasks, which he enters to his colleagues or students. The following text describes the design of the user interface and the database. I had solved this problem using the PHP framework Symfony, several scripts are written in Javascript, CSS framework Bootstrap was used to design the website. An important part of this work is user testing, data was obtained mainly through questionnaires, or personal consultation, and the results are in this thesis. After each testing phase, the existing version was improved based on the obtained data, bugs were fixed and the user interface was improved. The main benefit of the application is the simplification of assigning task to larger groups of people, it can be used for example by teachers or camp leaders. It will provide a quick overview of who has already fulfilled the tasks.
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Fingerprint Recognition with Graph Neural Networks
Pospíšil, Ondřej ; Špaňhel, Jakub (referee) ; Hradiš, Michal (advisor)
This thesis deals with the verification of fingerprints based on their graph representation. The proposed method uses a graph neural network and a combinatorial solver to obtain the matching between the minutae points of a pair of fingerprints. The matched minutae points are used to align the fingerprints using an estimated transformation by the RANSAC algorithm. The aligned fingerprints are processed by the SimGNN model. The resulting similarity score is then combined with the metrics obtained from the aligned fingerprints. The experiments summarize the selection of method parameters and the evaluation of fingerprint matching and verification accuracy. The contribution of this work is a new stable method of fingerprint alignment by solving the graph matching problem. The proposed verification method does not achieve high accuracy due to too few minutae attributes and poor discriminating power of the metrics used.
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Vehicle Following Distance Estimation from Mobile Phone in Vehicle
Zemánek, Ondřej ; Špaňhel, Jakub (referee) ; Sochor, Jakub (advisor)
The aim of this bachelor thesis is to create a mobile application for Android that estimates the distance of vehicles based on vehicle size in the camera image of the mobile phone. The estimation of the following distance is evaluated based on known camera parameters, the average vehicle width and the size of image area that represents detected car. Vehicles and their licences plates are detected in the image using cascade classifiers. Licence plate is detected only in the area of the detected vehicle. A training dataset for cascade classifier was created as part of this work. The cascade classifier is designed for vehicle detection. This work is extended with feature that tracks following distance in time and warns you with an acoustic signal on sudden distances change. This thesis is divided into five main parts - comparison of existing solutions for distance estimation, review of object detection methods, application design, implementation and evaluation of detectors, distance evaluation.
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Real-Time Face Tracking
Ermak, Aleksei ; Špaňhel, Jakub (referee) ; Hradiš, Michal (advisor)
This bachelor thesis focuses on the issue of face tracking in real time. In the beginning, this work describes the existing methods of object tracking and face detection. The following part of this thesis concentrates on the design, implementation and testing of the convolutional neural network, which was proved as the effective solution for the face tracking issue. In addition to this, the implemented network is compared to those existing methods. The last part of the thesis describes the optimization of the designed network using OpenVINO toolkit provided by Intel.
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Painting in 3D Space Using Augmented Reality
Kořínek, Milan ; Špaňhel, Jakub (referee) ; Beran, Vítězslav (advisor)
The goals of this work are described and create an application in which the user can paint in 3D space of virtual and augmented reality. First, the solution of the elements that provide the possibility of painting is clarified. It also describes the processing of the environment in which the user moves and interaction with the application. Finally, it is described how to combine individual parts of the solution with special hardware for a virtual and augmented reality.
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