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Title:Uporaba tehnologije za razpoznavo obraza na paketniku Direct4.me : diplomsko delo
Authors:ID Zorman, Lina (Author)
ID Holobar, Aleš (Mentor) More about this mentor... New window
ID Stropnik, Ambrož (Comentor)
Files:.pdf UN_Zorman_Lina_2021.pdf (901,47 KB)
MD5: 8D6D46A29440DB2FE2291D3870264CFD
PID: 20.500.12556/dkum/0b1a0dd1-7628-4b81-aa2c-d4418540bdee
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu smo preučili in ugotovili, ali so tehnologije za razpoznavo obraza že dovolj razvite, da bi bile primerne za uporabo na paketniku Direct4.me. Skozi podrobno raziskavo nekaterih najboljših že obstoječih algoritmov smo izbrali dva, ki sta se nam zdela najbolj primerna za naš primer uporabe ter ju podrobneje testirali. Za testiranje smo znotraj programa Visual Studio 2019 naredili konzolno aplikacijo, preko katere smo za vsak algoritem posebej preverjali njegovo delovanje na dveh množicah slik različnih ločljivosti. Rezultate smo predstavili v tabelah in jih analizirali ter na podlagi teh predlagali za našo rešitev primerno nizkocenovno strojno in programsko opremo.
Keywords:Pametni paketnik, razpoznava obraza, primerjava algoritmov, simulator
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[L. Zorman]
Year of publishing:2021
Number of pages:VIII, 57 str.
PID:20.500.12556/DKUM-80351 New window
UDC:004.932(043.2)
COBISS.SI-ID:87173891 New window
Publication date in DKUM:18.10.2021
Views:1047
Downloads:78
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:08.09.2021

Secondary language

Language:English
Title:The use of facial recognition technology on Direct4.me parcel locker
Abstract:In this diploma, we have studied and determined whether the current facial recognition technologies are suitable for use in the Direct4.me smart parcel locker. We studied some of the best existing algorithms and selected and further tested two of them. For testing purposes we made a console application in Visual Studio 2019. We tested both algorithms of sets of images of different resolutions and selected the algorithm with the optimal cost-performance compromise. We also studied and recommended the low-cost software and hardware that supports running the selected algorithm.
Keywords:Smart parcel locker, facial recognition, comparison of algorithms, simulator


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