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Title:Prepoznava prstov s pomočjo globokega učenja : magistrsko delo
Authors:ID Kopušar, Robert (Author)
ID Gleich, Dušan (Mentor) More about this mentor... New window
Files:.pdf MAG_Kopusar_Robert_2021.pdf (5,33 MB)
MD5: E734F30F2A0292AFCC4994AA3EF1222A
PID: 20.500.12556/dkum/b1ccb757-77b6-4ad8-9532-932d6f6f9aa5
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Magistrsko delo obravnava problematiko prepoznavanja prstov na roki, s pomočjo katere lahko v ozadju upravljamo najrazličnejše naloge in procese. Delo je zasnovano kot predstavitev reševanja iste problematike s pomočjo dveh različnih pristopov in predstavitev njunih prednosti in slabosti. Z uporabo tehnologije iskanja vzorca v sliki smo se problematike lotili na direkten način in v sliki sami iskali značilnost, s pomočjo katere smo iz slike razbrali tudi želeno gesto rok s prsti. Z uporabo tehnologije globokega učenja smo iskanje značilnosti prepustili umetni inteligenci, a smo zato na začetku potrebovali veliko bazo že rešenih primerov prepoznav. Dognanja iz tega dela dajejo dobra izhodišča vsem raziskovalcem in inženirjem pri nadaljnjemu raziskovanju in implementaciji sistemov slikovne prepoznave, ki temeljijo na tehnologiji strojnega vida ali globokega učenja.
Keywords:slikovno prepoznavanje, globoko učenje, LabVIEW, TensorFlow, prst
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[R. Kopušar]
Year of publishing:2021
Number of pages:X, 73 str.
PID:20.500.12556/DKUM-79172 New window
UDC:004.932:004.85(043.2)
COBISS.SI-ID:67960835 New window
Publication date in DKUM:21.06.2021
Views:1910
Downloads:120
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:19.05.2021

Secondary language

Language:English
Title:Finger recognition using deep learning
Abstract:The master‘s thesis describes hand fingers recognitions problematic, with which we could in a background manage different tasks and processes. It is designed to provide a solution of same problematic using two different approaches and provide theirs advantages and disadvantages. It directly analyzes this problematic using Pattern image matching technology. We were looking for a pattern in image, with which we could detect and classify hand fingers gesture. Using Deep learning technology, an artificial intelligence has been used to search for a pattern in image, but for this we needed a large image database with solved cases of fingers classification. Findings arising from this thesis give good basis to researchers and engineers to make further development and implementation of image recognitions systems based on Machine visions or Deep learning technology.
Keywords:image recognition, deep learning, LabVIEW, TensorFlow, finger


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