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» HITS is Principal Components Analysis
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89
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IJON
2007
94views more  IJON 2007»
15 years 11 days ago
A method for speeding up feature extraction based on KPCA
Kernel principal component analysis (KPCA) extracts features of samples with an efficiency in inverse proportion to the size of the training sample set. In this paper, we develop...
Yong Xu, David Zhang, Fengxi Song, Jing-Yu Yang, Z...
113
Voted
INFFUS
2002
87views more  INFFUS 2002»
15 years 8 days ago
Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images
In this paper, we propose a pixel level image fusion algorithm for merging Landsat thematic mapper (TM) images and SPOT panchromatic images. The two source images are first decomp...
Shutao Li, James T. Kwok, Yaonan Wang
88
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RAS
2007
113views more  RAS 2007»
15 years 2 days ago
Visual novelty detection with automatic scale selection
This paper presents experiments with an autonomous inspection robot, whose task was to highlight novel features in its environment from camera images. The experiments used two dif...
Hugo Vieira Neto, Ulrich Nehmzow
132
Voted

Publication
170views
14 years 11 months ago
Covariance Regularization for Supervised Learning in High Dimensions
This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...
Daniel L. Elliott, Charles W. Anderson, Michael Ki...
108
Voted
ICPR
2010
IEEE
14 years 10 months ago
Classification of Polarimetric SAR Images Using Evolutionary RBF Networks
This paper proposes an evolutionary RBF network classifier for polarimetric synthetic aperture radar ( SAR) images. The proposed feature extraction process utilizes the full covar...
Ince Turker, Serkan Kiranyaz, Moncef Gabbouj