Quality of sleep is an important attribute of an elder's health state and its assessment is still a challenge. The sleep pattern is a significant aspect to evaluate the quality of sleep, and how to recognize elder...
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ISBN:
(纸本)9783642163548
Quality of sleep is an important attribute of an elder's health state and its assessment is still a challenge. The sleep pattern is a significant aspect to evaluate the quality of sleep, and how to recognize elder's sleep pattern is an important issue for elder-care community. With the pressure sensor matrix to monitor the elder's sleep behavior in bed, this paper presents an unobtrusive sleep postures detection and patternrecognition approaches. Based on the proposed sleep monitoring system, the processing methods of experimental data and the classification algorithms for sleep patternrecognition are also discussed.
This paper presents a novel 3D face recognition method by means of the evolution of iso-geodesic distance curves. Specifically, the proposed method compares two neighboring iso-geodesic distance curves, and formalizes...
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ISBN:
(纸本)9781424442966
This paper presents a novel 3D face recognition method by means of the evolution of iso-geodesic distance curves. Specifically, the proposed method compares two neighboring iso-geodesic distance curves, and formalizes the evolution between them as a one-dimensional function, named evolution angle function, which is Euclidean invariant. The novelty of this paper consists in formalizing 3D face by an evolution angle functions, and in computing the distance between two faces by that of two functions. Experiments on Face recognition Grand Challenge (FRGC) ver2.0 shows that our approach works very well on both neutral faces and non-neutral faces. By introducing a weight function, we also show a very promising result on non-neutral face database.
In this paper, we report a classifier ensemble technique using the search capability of genetic algorithm (GA) for Named Entity recognition (NER) in biomedical domain. We use Maximum Entropy (ME) framework to build a ...
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ISBN:
(纸本)9780769542638
In this paper, we report a classifier ensemble technique using the search capability of genetic algorithm (GA) for Named Entity recognition (NER) in biomedical domain. We use Maximum Entropy (ME) framework to build a number of classifiers depending upon the various representations of a set of features. The proposed technique is evaluated with the JNLPBA 2004 data sets that yield the overall recall, precision and F-measure values of 67.98%, 71.68% and 69.78%, respectively.
Constructing proper descriptors for interest points is a critical aspect for local features related tasks in some computer vision and patternrecognition. This paper proposed to improve the SIFT descriptor by means of...
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ISBN:
(纸本)9781450304603
Constructing proper descriptors for interest points is a critical aspect for local features related tasks in some computer vision and patternrecognition. This paper proposed to improve the SIFT descriptor by means of combining the second derivative and the gradient magnitude, introducing the polar histogram orientation bin, as well as expending the regions for describing. We present a comparative evaluation of different descriptors and show that our approach provides better results than existing methods and the performance of our descriptors is also confirmed by excellent matching results. Copyright 2010 ACM.
We introduce the definition of fuzzy co-transform, as complementary to the definition of fuzzy transform and applied to co-domain of real functions. Basic properties of direct and inverse fuzzy co-transform are discus...
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We introduce the definition of fuzzy co-transform, as complementary to the definition of fuzzy transform and applied to co-domain of real functions. Basic properties of direct and inverse fuzzy co-transform are discussed. Examples of application to time series are given.
In this paper, it is shown how a Leaky Integrate and Fire (LIF) neuron can be applied to solve non-linear patternrecognition problems. Given a set of input patterns belonging to K classes, each input pattern is trans...
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Shape analysis is an active and important branch in computer vision research field. In recent years, many geometrical, topological, and statistical features have been proposed and widely used for shape-related applica...
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Theories on sphere-structure support vector machine (SVM) and multi-classification recognition algorithms were studied in the first place, and on this basis, in view of the issue of the difference in the hypersphere r...
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ISBN:
(纸本)9783642156205
Theories on sphere-structure support vector machine (SVM) and multi-classification recognition algorithms were studied in the first place, and on this basis, in view of the issue of the difference in the hypersphere radiuses resulted from the difference in the quantity of the training samples and the discrepancy in their distributions, the concepts of relative distance and weight were introduced, and subsequently a new algorithm of sphere-structure SVM multi-classification recognition was proposed on the basis of weighted relative distances. Accordingly, the data from the UCI database were used to conduct simulation experiments, and the results verified the validity of the algorithm propose.
The classification of sequences requires the combination of information from different time points. In this paper the detection of facial expressions is considered. Experiments on the detection of certain facial muscl...
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This paper presents a novel and efficient face recognition technique based on Local Binary pattern(LBP) with threshold for resolving traditional LBP's weakness of extracting global features. By setting a threshold...
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