• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Image Super-Resolution Using Generative Adversarial Networks

Student: Anton Lozhkov

Supervisor: Rimma Akhmetsafina

Faculty: Faculty of Computer Science

Educational Programme: Software Engineering (Bachelor)

Final Grade: 10

Year of Graduation: 2017

The goal of this work is to implement an algorithm for single image super-resolution using generative adversarial networks. In this paper, practical limitations of increasing image resolution using traditional methods are considered. In addition, modern solutions to this problem, with and without the use of convolutional neural networks, are described and compared. The advantages of Generative Adversarial Networks (GANs) over traditional convolutional neural networks are discussed, as well as network’s generator modifications that allow to achieve state-of-the-art results. A comparative study of the visual quality of the reconstructed images is carried out. The developed system allows the operator to experiment with various network hyperparameter configurations. The network itself is implemented with Theano and Lasagne. The trained models are then used in a web application that demonstrates the capabilities of the implemented algorithm. This paper contains 39 pages, 3 chapters, 20 illustrations, 3 tables, 38 bibliography items, 4 appendices.

Full text (added May 29, 2017)

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses