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Detection and Analysis of Violators in the Monitored Area
Sadílek, Jakub ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
The aim of this thesis is to create an internet application for detection and analysis of violators in the monitored area. Such an application then can be used for automated processing of records from security cameras or other captured videos from the guarded area. The first part of the work is focused on the theory of neural networks for object detection and classification in the image and recognition of people by their face. The next part describes used technologies for application development. The result is a client-server application with the possibility of configuration of processing, which allows detection of violators, identification of persons, object tracking and counting, path drawing, definition of the monitored area, usage of own detector, etc. Processed videos at the end can be played, downloaded or together with a list of detected violators shared on the internet via link.
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Detecting the Occurrence of Objects in a Video
Šamánek, Jan ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
This bachelor thesis deals with detection of objects in videos by using primarily convolution neural networks and creating simple user interface, which allows user to choose classification model and use it to analyze video or train given model on own dataset. First part is dedicated to description of machine learning and neural networks. After that follows the section about image description and image classification using machine learning algorithms and data augmentation. Last part deals with describtion of own design of neural network and user interface and describing achieved results.
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Remotely Managed Low-Energy Information Display
Petruška, Zdenko ; Mrázek, Vojtěch (referee) ; Goldmann, Tomáš (advisor)
The main goal of this thesis is to create visualization panel and an app used for management of content on this panel. Visualization panel is composed of a platform ESP32 and an E-ink display. The panel and the app communicate with each other using wireless connection. The app is written using Django web framework. The app provides management of multiple panels and displayed content can be shared by panels.
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Wearables Development Technologies for YSoft SafeQ
Stárek, Jan ; Goldmann, Tomáš (referee) ; Orság, Filip (advisor)
Wearable devices grew in popularity in recent years. This fact contributes to increasing efforts to expand mobile and other applications to wearable devices. Exploring these possibilities, this thesis summarizes information on wearable devices and their typical operating systems, including available tools and restrains these systems offer. Based on the conclusion of theoretical part of this thesis an application for wearable devices is designed and implemented, specifically an application for printers that operate via SafeQ system developed in Y Soft Corporation.
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Brute Force Attack on Access System Using Synthetic Fingerprints
Polehňa, Dominik ; Goldmann, Tomáš (referee) ; Kanich, Ondřej (advisor)
The work deals with the resistance of the VeriFinger comparison algorithm to synthetic fingerprints. The basics of fingerprints, comparison algorithms and synthetic fingerprint generators are gradually analyzed. In total, three experiments were designed to test the resistance of the algorithm using synthetic fingerprints. An application using the VeriFinger algorithm was implemented to evaluate individual experiments. A total of 2 800 000 synthetic fingerprints were generated across all experiments. The first experiment showed that random fingerprint generation was not effective for real fingerprints, but was somewhat sufficient for synthetic fingerprints. The second experiment proved that comparison and the comparison score could be used to estimate the class of the identified fingerprint, and in the third experiment, by narrowing the generation to one class, it raised the total number of matched fingerprints. The results of individual experiments were written and their possible extension was suggested.
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Face Recognition with Acceleration on the Neural Compute Stick
Horník, Matej ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
This bachelor thesis deals with current techniques for recognizing people by face. Convolutional neural networks are currently used for face recognition. In this work, convolutional neural networks will be described and also the architectures of convolutional networks used for face recognition will be compared. The goal will be to create a built-in system that will consist of a camera, a computing unit and a Neural Compute Stick accelerator. The system will recognize people by face with a freely available algorithm.
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Device for Monitoring of Air Quality
Jašek, Filip ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
The thesis deals with the design and implementation of air quality monitoring devic using selected sensors (RHT03, MQ-2, MQ-7) on STM Nucleo F446RE microcontroller platform. The next section describes the development of a mobile application to read out measured data using Bluetooth Low Energy created with the NativeScript framework primarily for the Android platform. Part of the thesis is the test operation of the measuring device and evaluation of the results.
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Face Recognition with Acceleration on the Neural Compute Stick
Horník, Matej ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
This bachelor thesis deals with current techniques for recognizing people by face. Convolutional neural networks are currently used for face recognition. In this work, convolutional neural networks will be described and also the architectures of convolutional networks used for face recognition will be compared. The goal will be to create a built-in system that will consist of a camera, a computing unit and a Neural Compute Stick accelerator. The system will recognize people by face with a freely available algorithm.
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Descriptor for Identification of a Person by the Face
Coufal, Tomáš ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
Thesis provides an overview and discussion of current findings in the field of biometrics. In particular, it focuses on facial recognition subject. Special attention is payed to convolutional neural networks and capsule networks. Thesis then lists current approaches and state-of-the-art implementations. Based on these findings it provides insight into engineering a very own solution based of CapsNet architecture. Moreover, thesis discussed advantages and capabilitied of capsule neural networks for identification of a person by its face.
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