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undergraduate thesis
Procjena značajki osoba na osnovi 3D dubinskih mjerenja niske rezolucije
Rijeka: University of Rijeka, Faculty of Engineering, 2018. urn:nbn:hr:190:339718
Dizdar, Matija
University of Rijeka
Faculty of Engineering
Department of Computer Engineering
Section of Software Engineering

Institutional repository: Repository of the University of Rijeka, Faculty of Engineering

Cite this document

Dizdar, M. (2018). Procjena značajki osoba na osnovi 3D dubinskih mjerenja niske rezolucije (Undergraduate thesis). Rijeka: University of Rijeka, Faculty of Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:190:339718

Dizdar, Matija. "Procjena značajki osoba na osnovi 3D dubinskih mjerenja niske rezolucije." Undergraduate thesis, University of Rijeka, Faculty of Engineering, 2018. https://urn.nsk.hr/urn:nbn:hr:190:339718

Dizdar, Matija. "Procjena značajki osoba na osnovi 3D dubinskih mjerenja niske rezolucije." Undergraduate thesis, University of Rijeka, Faculty of Engineering, 2018. https://urn.nsk.hr/urn:nbn:hr:190:339718

Dizdar, M. (2018). 'Procjena značajki osoba na osnovi 3D dubinskih mjerenja niske rezolucije', Undergraduate thesis, University of Rijeka, Faculty of Engineering, accessed 02 May 2024, https://urn.nsk.hr/urn:nbn:hr:190:339718

Dizdar M. Procjena značajki osoba na osnovi 3D dubinskih mjerenja niske rezolucije [Undergraduate thesis]. Rijeka: University of Rijeka, Faculty of Engineering; 2018 [cited 2024 May 02] Available at: https://urn.nsk.hr/urn:nbn:hr:190:339718

M. Dizdar, "Procjena značajki osoba na osnovi 3D dubinskih mjerenja niske rezolucije", Undergraduate thesis, University of Rijeka, Faculty of Engineering, Rijeka, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:190:339718

Metadata
TitleProcjena značajki osoba na osnovi 3D dubinskih mjerenja niske rezolucije
Title (english)Estimation of persons´ characteristics based on low-resolution 3D depth
AuthorMatija Dizdar
MentorDražen Brščić (mentor)
Committee memberKristijan Lenac (predsjednik povjerenstva)
GranterUniversity of Rijeka
Faculty of Engineering
(Department of Computer Engineering)
(Section of Software Engineering)
Rijeka
Defense date and country2018-09-18, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu dan je pregled konvolucijskih neuronskih mreža i autoenkodera. Takoder opisane su njihove implementacije koristeći Keras API i TensorFlow pozadinski sustav. Ispitane su mogućnosti klasifikacije i regresije uz podatke niske rezolucije koristeći standardne metrike. Dobiveni su i usporedeni rezultati treniranja sa i bez autoenkodera.
Abstract (english)
This thesis gives an overview of convolutional neural networks and autoencoders. Their implementations are described using the Keras API and TensorFlow backend. Given low resolution data, the performance of classification and regression is explored with respect to lowering resolution. Finally, the obtained results from training with and without an autoencoder are compared.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:190:339718
Study programmeTitle: Computer Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2018-10-02 08:03:18