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rdf:type
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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 (en)
- 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 (cs)
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Title
| - Rozpoznávání a třídění objektů podle tvaru
- Object Sorting Based on Shape (en)
- Rozpoznávání a třídění objektů podle tvaru (cs)
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skos:prefLabel
| - Rozpoznávání a třídění objektů podle tvaru
- Object Sorting Based on Shape (en)
- Rozpoznávání a třídění objektů podle tvaru (cs)
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skos:notation
| - RIV/00216305:26220/07:PU67880!RIV08-GA0-26220___
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http://linked.open.../vavai/riv/strany
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
| - P(GA102/06/0866), Z(MSM0021630503)
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/00216305:26220/07:PU67880
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - Neural Network, Back-propagation, Computer Vision (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - NOVÉ TRENDY V MIKROELEKTRONICKÝCH SYSTÉMECH A NANOTECHNOLOGIÍCH
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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http://linked.open...n/vavai/riv/zamer
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number of pages
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http://purl.org/ne...btex#hasPublisher
| - Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav fyziky
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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is http://linked.open...avai/riv/vysledek
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