National Repository of Grey Literature 49 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Deep Learning for OCR in GUI
Hamerník, Pavel ; Špaňhel, Jakub (referee) ; Lysek, Tomáš (advisor)
Optical character recognition (OCR) has been a topic of interest for many years. It is defined as the process of digitizing a document image into a sequence of characters. Despite decades of intense research, OCR systems with capabilities to that of human still remains an open challenge. In this work there is presented a design and implementation of such system, which is capable of detecting texts in graphical user interfaces.
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.
Pedestrian Attribute Analysis
Studená, Zuzana ; Špaňhel, Jakub (referee) ; Hradiš, Michal (advisor)
This work deals with obtaining pedestrian information, which are captured by static, external cameras located in public, outdoor or indoor spaces. The aim is to obtain as much information as possible. Information such as gender, age and type of clothing, accessories, fashion style, or overall personality are obtained using using convolutional neural networks. One part of the work consists of creating a new dataset that captures pedestrians and includes information about the person's sex, age, and fashion style. Another part of the thesis is the design and implementation of convolutional neural networks, which classify the mentioned pedestrian characteristics. Neural networks evaluate pedestrian input images in PETA, FashionStyle14 and BUT Pedestrian Attributes datasets. Experiments performed over the PETA and FashionStyle datasets compare my results to various convolutional neural networks described in publications. Further experiments are shown on created BUT data set of pedestrian attributes.
Ball Tracking in Sports Video
Motlík, Matúš ; Špaňhel, Jakub (referee) ; Bartl, Vojtěch (advisor)
This master's thesis deals with automatic detection and tracking of a soccer ball in sports videos. Based on the introduced techniques focusing on tracking of small objects in high-resolution videos, effective convolutional neural networks are designed and used by a modified version of tracking algorithm SORT for automatic object detection. A set of experiments with the processing of images in different resolutions and with various frequencies of detection extraction is carried out in order to examine the trade-off between processing speed and tracking accuracy. The obtained results of experiments are presented and used to form proposals for future work, which could lead to improvements in tracking accuracy while maintaining reasonable processing speed.
Action Game for GearVR
Mladý, Jakub ; Špaňhel, Jakub (referee) ; Herout, Adam (advisor)
This thesis deals with the study of technologies and techniques for creating virtual reality for mobile devices.  It includes a description of the design and implementation of an action game, using Unity Game Engine, which demonstrates Gear VR's capabilities well. The thesis describes the obstacles that arise in the creation of games for virtual reality as well as their possible solutions. Graphic elements of the game were developed based on the results of continuous user testing. Particular attention was paid to exploring the impact of visual effects and game elements used in games on a user in virtual reality.
Smart Loudspeaker with Raspberry Pi
Vondráček, Tomáš ; Špaňhel, Jakub (referee) ; Herout, Adam (advisor)
The bachelor thesis deals with the creation of music system that allows users to organize and play music in real time. The music system is based on client-server architecture and consists of server, web and mobile application. The server application serves as a music player and a connection broker among clients. The client serves as a user interface for the server, but can organize and play music on its own. The music system is implemented in JavaScript (ECMAScript 2018). The server application is built on the Node.js and implements Socket.IO server with REST API. The web application is based on React and presented as SPA. The mobile application is implemented in React Native with focus on Android system. The server and web applications are deployed on Heroku servers and Raspberry Pi computer. Mobile application is published on Google Play. The music system can be used for private music playback or as a means of organizing music among multiple users.
Pedestrian Identification
Jurča, Jan ; Špaňhel, Jakub (referee) ; Hradiš, Michal (advisor)
This thesis deals with pedestrian identification from video sequence based on person, face and gait recognition. For person and face recognition are used pretrained networks. While for gait recognition is implemented and compared many different networks. Final pedestrian recognition is based on multimodal fusion realized by neural network. For the purpose of the work was created dataset, along with a set of tools that allow its almost automatic creation.
Holistic License Plate Recognition Based on Convolution Neural Networks
Le, Hoang Anh ; Hradiš, Michal (referee) ; Špaňhel, Jakub (advisor)
Main goal of this work was to create a holistic license plate reader, with an emphasis on achieving the highest possible accuracy on low quality images. Combination of convolutional and recurrent neural networks was designed and implemented, with usage of LSTM and CTC, where the inputs are cut-outs from the entire license plate. Competitive networks were also implemented to compare results. Networks were compared on a total of 4 datasets and the results were, that my design has achieved the best results with a recognition accuracy of 97.6%.
Vehicle License Plate Detection and Recognition Software
Masaryk, Adam ; Hradiš, Michal (referee) ; Špaňhel, Jakub (advisor)
The aim of this bachelor thesis is to design and develop software that can detect and recognize license plates from images. The software is divided into 3 parts - license plates detection, detector output processing and license plates characters recognition. We decided to implement detection and recognition using modern methods using convolutional neural networks.
Traffic Violation Detection on Crossroads
Karpíšek, Miroslav ; Bartl, Vojtěch (referee) ; Špaňhel, Jakub (advisor)
This bachelor thesis presents procedure for the detection of red-light violation. In the theoretical part of the thesis, the current solution aproaches used in image processing are described. The practical part focuses on creation of program for automatic traffic corridors detection, vehicle tracking and the current traffic light state detection. The results obtained by experimenting with the proposed procedure and the possibilities of its further improvement are also discussed.

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