magistrsko delo
Povzetek
Problem odčitavanja vrednosti analognih instrumentov z uporabo metod računalniškega vida je star problem, ki je bil že rešen z mnogimi različnimi pristopi. Zaradi zahteve podjetja po ponovni implementaciji starega algoritma, sta se nam pojavili dve vprašanji: Kako bi lahko problem rešili z uporabo najsodobnejših pristopov in kako dobro se ti novi pristopi primerjajo z obstoječimi starimi pristopi.
V tej diplomski nalogi so predlagane tri metode, kjer vsaka poizkuša problem rešiti na svojevrsten način. Prva metoda je le ponovna implementacija in temelji na podlagi starih metod. Drugi dve metodi pa uporabljata umetno inteligenco in temeljita na nevronskih omrežjih VGG-16 in Mask R-CNN. V nalogi poleg opisov metod, te tudi implementiramo in med seboj primerjamo.
Ključne besede
nevronska omrežja;magisteriji;
Podatki
Jezik: |
Slovenski jezik |
Leto izida: |
2021 |
Tipologija: |
2.09 - Magistrsko delo |
Organizacija: |
UL FE - Fakulteta za elektrotehniko |
Založnik: |
[A. Bertoncelj] |
UDK: |
004.93:621.317.7(043.2) |
COBISS: |
107176195
|
Št. ogledov: |
161 |
Št. prenosov: |
55 |
Ocena: |
0 (0 glasov) |
Metapodatki: |
|
Ostali podatki
Sekundarni jezik: |
Angleški jezik |
Sekundarni naslov: |
Reading displays of measuring instruments using computer vision and machine learning methods |
Sekundarni povzetek: |
The problem of reading values from analogue instruments using comptures vision methods is an old problem that has already been solved many times using various methods. A request to re-implement the algorithm led to us ask ourself two questions: how could the problem be solved using state-of-the-art approaches, and how well do these new approaches compare with the existing old ones.
In this thesis, three methods are presented, each trying to solve the problem of in a different way. The first method is just a re-implementation and upgrade of existing methods. However, the other two methods use artificial intelligence and are based on two different neural networks VGG-16 and Mask R-CNN. In addition to describing the methods, we also implement them and compare their results. |
Sekundarne ključne besede: |
analogue measuring instruments;computer vision;machine learning;neural networks;computer science;master's degree;Merilni instrumenti;Računalniški vid;Strojno učenje;Računalništvo;Univerzitetna in visokošolska dela; |
Vrsta dela (COBISS): |
Magistrsko delo/naloga |
Študijski program: |
1001017 |
Konec prepovedi (OpenAIRE): |
1970-01-01 |
Komentar na gradivo: |
Univ. v Ljubljani, Fak. za računalništvo in informatiko |
Strani: |
90 str. |
ID: |
15129360 |