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Orthogonal forward selection for constructing the radial basis function network with tunable nodes
An orthogonal forward selection (OFS) algorithm based on the leave-one-out (LOO) criterion is proposed for the construction of radial basis function (RBF) networks with tunable nodes. This OFS-LOO algorithm is computationally efficient and is capable of identifying parsimonious RBF networks that generalise well. Moreover, the proposed algorithm is fully automatic and the user does not need to specify a termination criterion for the construction process
Effect of high fat diets on the mRNA expression of PPAR-alpha and its target genes after fasting
Activation of Peroxisome Proliferator-Activated Receptor alpha by a polar fraction isolated from oxidized frying oil
Comparing Different Template Features for Recognizing People by Their Gait
To recognize people by their gait from a sequence of images, we have proposed a statistical approach which combined eigenspace transformation (EST) with canonical space transformation (CST) for feature transformation of spatial templates. This approach is used to reduce data dimensionality and to optimize the class separability of different gait sequences simultaneously. Good recognition rates have been achieved. Here, we incorporate temporal information from optical flows into three kinds of temporal templates and use them as features for gait recognition in addition to the spatial templates. The recognition performance for four kinds of template features has been evaluated in this paper. Experimental results show that spatial templates, horizontal-flow templates and the combined horizontal-flow and vertical-flow templates are better than vertical-flow templates for gait recognition
C.J. Koch (1932 - )
Biographical, bibliographical, and literary historiography of Australian author C.J. Koch
Functions of the C-terminal region of chitinase ChiCW from Bacillus cereus 28-9 in substrate-binding and hydrolysis of chitin
High-level expression and characterization of two chitinases, ChiCH and ChiCW, of Bacillus cereus 28-9 in Escherichia coli
Recognizing humans by gait using a statistical approach for temporal templates
In this paper, we propose a new approach which combines canonical space transformation (CST) with the eigenspace transformation (EST) for feature extraction of temporal templates in a gait sequence. Eigenspace transformation has been demonstrated to be a potent metric in automatic face recognition and gait analysis, but without using data analysis to increase classification capability. Our method can be used to reduce data dimensionality and to optimize the class separability of different gait sequences simultaneously. Each temporal template is projected from high-dimensional image space to a single point in low-dimensional canonical space. In this new space the recognition of human gait by template matching becomes much faster and simpler. Experimental results for human gait analysis show this method is superior to eigenspace representation. As such, the combination of EST and CST is shown to be of considerable advantage in an emerging new biometric
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