Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related disciplines. The document describes also MemBrain application environment as a powerful and easy to use neural networks’ editor and simulator supporting ANN.
Słowa kluczowe
Wydawca
Rocznik
Tom
Strony
54--59
Opis fizyczny
Bibliogr. 5 poz., fig.
Twórcy
autor
- Fundamentals of Technology Faculty, Lublin University of Technology, ul. Nadbystrzycka 38, 20-618 Lublin, Poland
autor
- Management Faculty, Lublin University of Technology, ul. Nadbystrzycka 38, 20-618 Lublin, Poland
autor
- University of Maria Curie Sklodowska, Multimedia Communications Lab. 20-011 Lublin ul. Narutowicza 12, Poland
Bibliografia
- 1. Balabin R.M., Lomakina E.I.: Neural network approach to quantum-chemistry data: Accurate prediction of density functional theory energies. J. Chem. Phys., 131(7), 2009: 74-104.
- 2. Shrivastava V., Sharma N.: Artificial Neural Network Based Optical Character Recognition. Signal & Image Processing. An International Journal (SIPIJ), 3(5), 2012.
- 3. Basu J. K., Bhattacharyya D., Kim T.: Use of Artificial Neural Network in Pattern Recognition. International Journal of Software Engineering and Its Applications, 4(2), 2010.
- 4. Dung L., Mizukawa M.: Designing a Pattern Recognition Neural Network with a Reject Output and Many Sets of Weights and Biases. Pattern Recognition Techniques, Technology and Applications, 2008.
- 5. http://www.membrain-nn.de/english/details_en.htm (May 2013).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-137d9a17-8260-471f-a377-e9acdbff3d6f