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Atvirkštinio skleidimo neuroziniai tinklai : vaizdų atpažinimas / Backpropagation neural networks: pattern recognition

In this Master’s degree work artificial neural networks and back propagation learning algorithm for human faces and pattern recognition are analyzed.
In the second part of work artificial neural networks and their architecture and structures models are analyzed. In the third part of article the backpropagation procedure and procedures theoretical learning principle are analyzed. In the fourth part different kinds of ANN methods and patterns extracting methods in recognition, learning and classification use were researched. In this part RGB method for patterns features extraction was described. In the fifth part the requirements specification, prototype model, use case diagram, system architecture, programs modules and objects project for software realization were created. In the same part backpropagation procedures running principle was realized. After the project part was completed, a face and patterns recognition system was created. In the sixth part the created software system was tested. According to the testing results software’s recognition rate is 82,5 % using supervised learning and 82,8 % using unsupervised learning. We found using the FAR and FRR rates the ERR rate, which was 40 %. While doing the testing with changed human characteristics, the system showed 84,6 % recognition rate. This rate shows very good work of the system by a little bit changed human characteristics. Systems realization was evaluated by users as very good one. In the seventh part software’s... [to full text]

Identiferoai:union.ndltd.org:LABT_ETD/oai:elaba.lt:LT-eLABa-0001:E.02~2005~D_20050528_172344-92726
Date28 May 2005
CreatorsStudenikin, Oleg
ContributorsLenkevičius, Antanas, Rutkauskienė, Danguolė, Rudžionis, Vytautas, Kavaliauskas, Kazys, Tamošiūnaitė, Minija, Paradauskas, Bronius, Rubliauskas, Dalius, Targamadzė, Aleksandras, Matickas, Jonas Kazimieras, Kaunas University of Technology
PublisherLithuanian Academic Libraries Network (LABT), Kaunas University of Technology
Source SetsLithuanian ETD submission system
LanguageLithuanian
Detected LanguageEnglish
TypeMaster thesis
Formatapplication/pdf
Sourcehttp://vddb.library.lt/obj/LT-eLABa-0001:E.02~2005~D_20050528_172344-92726
RightsUnrestricted

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