Duboke neuronske mreže

master's thesis

• Author: Nikola Jelić
• Mentor: Saša Singer (mentor)
• Committee member: Saša Singer (predsjednik povjerenstva)
• Committee member: Robert Manger (član povjerenstva)
• Committee member: Goranka Nogo (član povjerenstva)
• Committee member: Zvonimir Bujanović (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Mathematics); Zagreb
• Defense date and country: 2020-07-20, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Mathematics

Abstract

Duboke neuronske mreže su sve popularnije zahvaljujući velikim količinama podataka, većoj snazi računala te zajednici okruženoj oko softverskih alata. Koriste se za obradu računalnog vida, prirodnog jezika, tekstova te raznih predikcija. U ovom radu najprije opisujemo općeniti pojam neuronske mreže te neophodne segmente za učenje modela, a to su: podaci, mjere uspješnosti, arhitektura modela i algoritmi učenja. Dalje se uvode i analiziraju optimizacijski algoritmi, mrežne arhi- tekture i njihove primjene. Na kraju se pokazuje važnost dubine neuronskih mreža, rješenjem problema klasi.

Abstract (english)

Deep neural networks are becoming popular because of a large amount of existing data, increased computing power as well as the community created around the software. Networks are used for computer vision, natural language processing and various predictions. This thesis, firstly describes the general concept of a neural network and the necessary segments for model learning, of which there are four: data, performance measures, model architecture and learning algorithms. Optimization algorithms, network architectures and their applications are further introduced and analyzed. Finally, the importance of the depth is shown by solving the problem of classifying images of handwritten characters.

• Keywords: duboke neuronske mreže; obrada računalnog vida; obrada prirodnog jezika; obrada tekstova; predikcije
• Keywords (english): deep neural networks; computer vision; natural language processing; word processing; various predictions
• Language: croatian
• URN:NBN: urn:nbn:hr:217:612053
• Study programme: Title: Computer Science and Mathematics; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra računarstva i matematike (magistar/magistra računarstva i matematike)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2020-11-25 13:01:44