prikaz prve stranice dokumenta Neuronske mreže u OpenCV biblioteci
  Download
PDF 842.07 KB
undergraduate thesis
Neuronske mreže u OpenCV biblioteci
Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2016. urn:nbn:hr:200:991934
Marković, Bože Eugen
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Computer Engineering and Automation
Chair of Automation and Robotics

Cite this document

Marković, B. E. (2016). Neuronske mreže u OpenCV biblioteci (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:991934

Marković, Bože Eugen. "Neuronske mreže u OpenCV biblioteci." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2016. https://urn.nsk.hr/urn:nbn:hr:200:991934

Marković, Bože Eugen. "Neuronske mreže u OpenCV biblioteci." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2016. https://urn.nsk.hr/urn:nbn:hr:200:991934

Marković, B. E. (2016). 'Neuronske mreže u OpenCV biblioteci', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 22 September 2023, https://urn.nsk.hr/urn:nbn:hr:200:991934

Marković BE. Neuronske mreže u OpenCV biblioteci [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2016 [cited 2023 September 22] Available at: https://urn.nsk.hr/urn:nbn:hr:200:991934

B. E. Marković, "Neuronske mreže u OpenCV biblioteci", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2016. Available at: https://urn.nsk.hr/urn:nbn:hr:200:991934

Please login to the repository to save this object to your list.
Metadata
TitleNeuronske mreže u OpenCV biblioteci
Title (english)Neural networks in OpenCV library
AuthorBože Eugen Marković
MentorDamir Filko (mentor)
Committee memberDamir Filko (predsjednik povjerenstva)
Committee memberHrvoje Glavaš (član povjerenstva)
Committee memberDamir Blažević (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Computer Engineering and Automation)
(Chair of Automation and Robotics)
Osijek
Defense date and country2016-09-28, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Process Computing
Abstract
Cilj ovog završnog rada bio je prikazati teorijsku podlogu umjetnih neuronskih mreža i njihovu primjenu u C++ programskom jeziku sa OpenCV bibliotekom. Obrađeni problem je prepoznavanje ljudskog rukopisa, točnije znamenaka. Potrebno je stvoriti neuronsku mrežu i definirati njene parametre što se postiže s klasama i funkcijama iz implementirane OpenCV biblioteke. Pokreće se proces učenja neuronske mreže sa što većim brojem uzoraka. Kad je proces treniranja gotov sustavu se predaju testni uzorci kako bi se utvrdila uspješnost procesa učenja. U simulaciji je mreža trenirana sa 1000 uzoraka, a testnih primjera predano joj je 100. Od 100 uzoraka prepoznato ih je 83 što bi značilo da je uspješnost na relativno visokoj razini.
Abstract (english)
The aim of this bachelor thesis was to show the theoretical basis of artificial neural networks and their use in C ++ programming language with OpenCV library. Problem that was processed is human handwriting recognition, digits. It is necessary to create a neural network and define its parameters using classes and functions from the OpenCV library. The process of learning neural network is initiated with training samples. When the training process is finished, test samples are used in order to determine the success of the learning process. In the simulation, the network is trained with a 1000 samples and given a 100 test examples. Of the 100 samples, 83 were identified, which would mean that the success rate is relatively high.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:991934
Study programmeTitle: Undergraduate University Study Programme in Computer Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
RepositoryFaculty of Electrical Engineering, Computer Science and Information Technology Osijek
Created on2016-11-07 11:23:48