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Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F07%3APU67880%21RIV08-GA0-26220___
rdf:type
skos:Concept n22:Vysledek
dcterms:description
This paper presents modern science appears from the basis of Computer Vision and classifier of Synthetic Neural Network. A picture of watched object has to be taken in high quality with the best lighting and camera has to be situated vertically upon the object. Different camera positions does not assure exact results. Subsequently, image has to be transformed into binary image and purged from noise and other interference. Moments are used to describe separate objects in picture. Via the central moments and normed moments I count seven moments characteristic for each object to be identified. These moments are practically independent on rotation or changing scale of the object. They fluctuate only in a short spread. It is input to Neural Network, which is used as the classifier. The system of Back-propagation is used as the Neural Network with type of learning called learning with teacher. In my work, each letter of alphabet is used as the object to be identified. Further, I tried to identify object by This paper presents modern science appears from the basis of Computer Vision and classifier of Synthetic Neural Network. A picture of watched object has to be taken in high quality with the best lighting and camera has to be situated vertically upon the object. Different camera positions does not assure exact results. Subsequently, image has to be transformed into binary image and purged from noise and other interference. Moments are used to describe separate objects in picture. Via the central moments and normed moments I count seven moments characteristic for each object to be identified. These moments are practically independent on rotation or changing scale of the object. They fluctuate only in a short spread. It is input to Neural Network, which is used as the classifier. The system of Back-propagation is used as the Neural Network with type of learning called learning with teacher. In my work, each letter of alphabet is used as the object to be identified. Further, I tried to identify object by This paper presents modern science appears from the basis of Computer Vision and classifier of Synthetic Neural Network. A picture of watched object has to be taken in high quality with the best lighting and camera has to be situated vertically upon the object. Different camera positions does not assure exact results. Subsequently, image has to be transformed into binary image and purged from noise and other interference. Moments are used to describe separate objects in picture. Via the central moments and normed moments I count seven moments characteristic for each object to be identified. These moments are practically independent on rotation or changing scale of the object. They fluctuate only in a short spread. It is input to Neural Network, which is used as the classifier. The system of Back-propagation is used as the Neural Network with type of learning called learning with teacher. In my work, each letter of alphabet is used as the object to be identified. Further, I tried to identify object by
dcterms:title
Rozpoznávání a třídění objektů podle tvaru Object Sorting Based on Shape Rozpoznávání a třídění objektů podle tvaru
skos:prefLabel
Object Sorting Based on Shape Rozpoznávání a třídění objektů podle tvaru Rozpoznávání a třídění objektů podle tvaru
skos:notation
RIV/00216305:26220/07:PU67880!RIV08-GA0-26220___
n3:strany
121-125
n3:aktivita
n11:Z n11:P
n3:aktivity
P(GA102/06/0866), Z(MSM0021630503)
n3:dodaniDat
n4:2008
n3:domaciTvurceVysledku
n18:5802407
n3:druhVysledku
n19:D
n3:duvernostUdaju
n8:S
n3:entitaPredkladatele
n6:predkladatel
n3:idSjednocenehoVysledku
448499
n3:idVysledku
RIV/00216305:26220/07:PU67880
n3:jazykVysledku
n16:cze
n3:klicovaSlova
Neural Network, Back-propagation, Computer Vision
n3:klicoveSlovo
n9:Computer%20Vision n9:Back-propagation n9:Neural%20Network
n3:kontrolniKodProRIV
[CA2C63C7E435]
n3:mistoKonaniAkce
Brno
n3:mistoVydani
Brno
n3:nazevZdroje
NOVÉ TRENDY V MIKROELEKTRONICKÝCH SYSTÉMECH A NANOTECHNOLOGIÍCH
n3:obor
n20:JD
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:projekt
n17:GA102%2F06%2F0866
n3:rokUplatneniVysledku
n4:2007
n3:tvurceVysledku
Tofel, Pavel
n3:typAkce
n12:CST
n3:zahajeniAkce
2007-01-19+01:00
n3:zamer
n21:MSM0021630503
s:numberOfPages
5
n7:hasPublisher
Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav fyziky
n14:isbn
978-80-7355-075-2
n15:organizacniJednotka
26220