Efficient and accurate image alignment using TSK-type neuro-fuzzy network with data-mining-based evolutionary learning algorithm

Image alignment is considered a key problem in visual inspection applications. The main concerns for such tasks are fast image alignment with subpixel accuracy. About this, neural network-based approaches are very popular in visual inspection because of their high accuracy and efficiency of aligning...

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Vydáno v:	EURASIP journal on advances in signal processing Ročník 2011; číslo 1; s. 1 - 22
Hlavní autoři:	Hsu, Chi-Yao, Cheng, Yi-Chang, Lin, Sheng-Fuu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.12.2011 Springer Nature B.V
Témata:	Algorithms Alignment Data mining Engineering Evolutionary Fuzzy systems Learning Neural networks Quantum Information Technology Signal,Image and Speech Processing Spintronics subpixel accuracy data-mining based evolutionary learning algorithm regularized least square TSK-type neuro-fuzzy network
ISSN:	1687-6180, 1687-6172, 1687-6180
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