id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_yn7bzumlpjdarpfazw5wvrnhwq	Turker Ince	Evolutionary RBF classifier for polarimetric SAR images	2012	8	.pdf	application/pdf	6259	680	58	In this paper, a robust radial basis function (RBF) network based classifier is proposed for polarimetric decomposition based pixel values with textural information (contrast, correlation, energy, and homogeneity) in the feature set, and employing automated evolutionary RBF classifier for the pattern recognition (1999) proposed a new unsupervised classification method based on combination of polarimetric target decomposition (Cloude & Pottier, 1997) and the maximum likelihood Earlier work on RBF classifiers for polarimetric SAR image classification Overview of the evolutionary RBF network classifier design for polarimetric SAR image. In order to test robustness of the proposed RBF network classifier trained by the MD-PSO based dynamic clustering, 20 independent runs are performed over the San Francisco area image and the Next, the proposed evolutionary RBF classifier with the suggested feature set has been applied to the polarimetric image of pixels with 11 identified crop classes {stem beans, potatoes, lucerne, wheat, peas, sugar beet, rape seed, grass, forest, bare soil,	./cache/work_yn7bzumlpjdarpfazw5wvrnhwq.pdf	./txt/work_yn7bzumlpjdarpfazw5wvrnhwq.txt