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

Landmark Recognition in Photos

Student: Andrei Smirdin

Supervisor: Denis Moskvin

Faculty: St. Petersburg School of Physics, Mathematics, and Computer Science

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Final Grade: 10

Year of Graduation: 2020

Deep learning has become the most popular approach for solving image retrieval and recognition problems. In particular, significant results were achieved for the task of landmark recognition. However, most existing systems do not solve it directly but use the results of solving the retrieval problem. These solutions achieve high recognition accuracy, but they have longer inference time and use more memory. This work describes a way to build a system for landmark classification, which allows to avoid intermediate stages and is faster during inference. A described system can perform classification without location information - only by photo, however, the presence of location information increases the accuracy of recognition. To train the deep neural network, a dataset containing photos depicting landmarks that Odnoklassniki users uploaded to the network was built. The process of building the dataset is fully automated and does not require additional human assessment. Keywords: deep learning, image classification, landmark recognition.

Full text (added May 28, 2020)

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