Thesis Details
Rekonstrukce snímku obličeje s využitím neuronových sítí
The main purpose of this bachelor's thesis is to propose and implement a model, using neural networks, that will be able to reconstruct low-resolution facial images with blurry parts of the face. The task of super-resolution of facial images is solved by two models based on convolutional neural networks. The first model is built upon the architecture of ResNet whereas the other model makes use of the principles of generative adversarial networks. The proposed models are implemented in the Python programming language with the use of application programming interface of the TensorFlow framework. Moreover, as a part of this work, an application with a simple grafical user interface was created. This application makes it easy to use the implemented models. Several experiments are analyzed in the last chapter of this thesis to evaluate the performance of the models.
CCTV, camera, image reconstruction, artificial intelligence, convolutional neural networks, generative adversarial networks, ResNet, TensorFlow
Fučík Otto, doc. Dr. Ing. (DCSY FIT BUT), člen
Holík Lukáš, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Szőke Igor, Ing., Ph.D. (DCGM FIT BUT), člen
Veselý Vladimír, Ing., Ph.D. (DIFS FIT BUT), člen
@bachelorsthesis{FITBT21391,
author = "Petr Zubal\'{i}k",
type = "Bachelor's thesis",
title = "Rekonstrukce sn\'{i}mku obli\v{c}eje s vyu\v{z}it\'{i}m neuronov\'{y}ch s\'{i}t\'{i}",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2019,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/21391/"
}