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Assembly Neural Network with Nearest-Neighbor Recognition Algorithm
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SYSNO ASEP 0405597 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Assembly Neural Network with Nearest-Neighbor Recognition Algorithm Title Skládané neuronové sítě s rozpoznávacím algoritmem nejbližšího souseda Author(s) Goltsev, A. (UA)
Húsek, Dušan (UIVT-O) RID, SAI, ORCID
Frolov, A. (RU)Source Title Neural Network World. - : Ústav informatiky AV ČR, v. v. i. - ISSN 1210-0552
Roč. 15, - (2005), s. 9-22Number of pages 14 s. Language eng - English Country CZ - Czech Republic Keywords assembly neural network ; unsupervised learning ; binary Hebbian rule ; pattern recognition ; texture segmentation ; classification Subject RIV BA - General Mathematics R&D Projects 1M0567 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) UT WOS 000232532100002 EID SCOPUS 14744271397 Annotation An assembly neural network based on binary Hebbian rule is suggested for pattern recognition. The network consists of several sub-networks according to the number of classes to be recognized. Each sub-network consists of several neural columns according to dimensionality of signal space so that the value of each signal component is encoded by activity of adjacent neurons of the column. A new recognition algorithm is presented which realizes the nearest-neighbor method in the assembly neural network. Computer simulation of the network is performed. The model is tested on a texture segmentation task. The experiments have demonstrated that the network is able to segment reasonably real-world texture images. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2006
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