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Invariant pattern classification neural network versus FT approachDobnikar, Andrej ...Invariant Pattern Classification (IPC) of black and white images is studied in two directions. Classical Fourier Transform (FT) approach consists of normalisation procedure for excluding ... magnification or size influence and FT transforms, whose output spectrum descriptors are invariant to rotation and/or translation. Only pattern calssification independent of size and rotation is concerned in this paper. It is supposed that the observed object is placed in the center of the image. An alternative approach uses Neural Network Modeling (NNM) to achieve the same effect. It is shown that the proposed Neural Network with the combination of dynamic and associative properties better solves the same problem with additional potential capability of considerable higher parallel processing.Source: Microprocessing and microprogramming. - ISSN 0165-6074 (Vol. 33, no. 3, 1992, str. 161-168)Type of material - article, component partPublish date - 1992Language - englishCOBISS.SI-ID - 1806187
Author
Dobnikar, Andrej |
Ficzko, Jelena |
Podbregar, Damjan |
Rezar, Uroš
Topics
računalništvo |
računalniške arhitekture |
podatkovno vodeni računalniki |
makro podatkovno vodeni računalniki |
integrirano programsko okolje |
IPRESPS |
časovno kritične aplikacije |
DFCL |
realni čas |
sistemi v realnem času |
dekompozicija |
razvrščanje |
paralelno procesiranje |
grafi |
computer science |
pattern classification |
invariance to size and rotation |
normalization |
FT |
associative neural network |
dynamic neural network
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Database name | Field | Year |
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Dobnikar, Andrej | 02272 |
Ficzko, Jelena | 11148 |
Podbregar, Damjan | 18552 |
Rezar, Uroš |
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