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Title:Razvoj mobilne aplikacije za sledenje športnim aktivnostim v fitnes centrih : diplomsko delo
Authors:ID Lang, Timotej (Author)
ID Fister, Iztok (Mentor) More about this mentor... New window
Files:.pdf UN_Lang_Timotej_2023.pdf (2,17 MB)
MD5: CE4E1F3AB4659C22E5FAD0516742F19D
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomski nalogi je predstavljena mobilna aplikacija za sledenje napredka in športnim aktivnostim v fitnes centrih, ki vsebuje model strojnega učenja, ki uporabniku omogoča planiranje in sledenje napredka. Model zajema podatke tedensko porabljenih kalorij iz opravljenih treningov uporabnika, s katerimi predvidi količino porabljenih kalorij s fitnes aktivnostmi tekom naslednjega tedna. Mobilno aplikacijo podpira operacijski sistem Android, za katerega je implementiran uporabniku prijazen grafični vmesnik.  
Keywords:Kotlin, fitnes, strojno učenje, mobilna aplikacija
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[T. Lang]
Year of publishing:2023
Number of pages:1 spletni vir (1 datoteka PDF (IX, 46 f.))
PID:20.500.12556/DKUM-84496 New window
UDC:004.777:004.85(043.2)
COBISS.SI-ID:168286723 New window
Publication date in DKUM:12.07.2023
Views:1293
Downloads:207
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:14.06.2023

Secondary language

Language:English
Title:Development of a mobile application for tracking sports activities in fitness centers
Abstract:The diploma thesis presents a mobile application for tracking progress and sports activities in fitness centres, which includes a model of machine learning that allows the user to plan and track progress. The model includes weekly calories burned data from the user's completed workouts to predict the amounts of calories consumed during the following week's fitness activities. The mobile application supports the Android operating system with a user-friendly graphical interface implemented.
Keywords:Kotlin, fitness, machine learning, mobile application


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