In this paper, we demonstrate how one-class recognition of cognitive brain functions across multiple subjects can be performed at the 90% level of accuracy via an appropriate choices of features which can be chosen au...
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ISBN:
(纸本)9783642167720
In this paper, we demonstrate how one-class recognition of cognitive brain functions across multiple subjects can be performed at the 90% level of accuracy via an appropriate choices of features which can be chosen automatically. The importance of this work is that while one-class is often the appropriate classification setting for identifying cognitive brain functions, most work in the literature has focused on two-class methods. Our work extends one-class work by [1], where such classification was first shown to be possible in principle albeit with an accuracy of about 60%. The results are also comparable to work of various groups around the world e. g.[2], [3] and [4] which have concentrated on two-class classification. The strengthening in the feature selection was accomplished by the use of a genetic algorithm run inside the context of a wrapper approach around a compression neural network for the basic one-class identification. In addition, versions of one-class SVM due to [5] and [6] were investigated.
The proceedings contain 51 papers. The topics discussed include: a fast algorithm in exponential change-points model with comparison;managing distributed temperature measurements in an embedded system of a 3-phase 10 ...
ISBN:
(纸本)9780769542690
The proceedings contain 51 papers. The topics discussed include: a fast algorithm in exponential change-points model with comparison;managing distributed temperature measurements in an embedded system of a 3-phase 10 kVA energy efficient switchable distribution transformer employing a modular approach;software development for black tea's physical variable and quality class relationship analyzing using correlation adaptive visual patternrecognition artificial neural network based expert system: proof of concept of auto parameter choosing expert system;maximum power point tracking based optimal control wind energy conversion system;fabrication and characterization of dye-sensitized solar cell using blackberry dye and titanium dioxide nanocrystals;using pattern matching in the 1-D domain of chain code signals for the compression of binary printed Farsi and Arabic textual images;and image enhancement and image restoration for old document image using genetic algorithm.
The Chinese text in natural scene images which are transmitted in mobile communication network usually contains various and important information. Therefore, capturing Chinese text in these images can analyze the cont...
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Hot events detection in text streams has drawn increasing attention in recent sequential data mining works. Different from traditional TDT task which find all the real events' cluster, hot events detection only id...
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The multilevel thresholding is an important technique for image processing and patternrecognition. The maximum entropy thresholding has been widely applied in the literature. In this paper, a new multilevel MET algor...
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To date many activity spotting approaches are static: once the system is trained and deployed it does not change anymore. There are substantial shortcomings of this approach, specifically spotting performance is hampe...
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We present an efficient method based on image rectification for achieving the feature correspondence between images. The method is comprehensible through a geometric analysis of two rectified views. An important const...
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Matching of partial fingerprints has important applications in both biometrics and forensics. It is well-known that the accuracy of minutiae-based matching algorithms dramatically decreases as the number of available ...
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This paper presents a novel local feature descriptor, the Local Directional pattern (LDP), for describing local image feature. A LDP feature is obtained by computing the edge response values in all eight directions at...
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In this paper we present a variation of the Cocke-Younger-Kasami algorithm (CYK algorithm for short) for the analysis of fuzzy free context languages applied to DNA strings. We propose a variation of the original CYK ...
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ISBN:
(纸本)9783642167720
In this paper we present a variation of the Cocke-Younger-Kasami algorithm (CYK algorithm for short) for the analysis of fuzzy free context languages applied to DNA strings. We propose a variation of the original CYK algorithm where we prove that the order of the new CYK algorithm is O(n). We prove that the new algorithm only use 2n-1 memory localities. We use a variation of the CYK algorithm, where the free context language can be fuzzy. The fuzzy context-free grammar (FCFG) is obtained from DNA and RNA sequences.
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