Single nucleotide polymorphisms (SNPs) are the most common form of genetic variant in humans, which can be generally classified into disease related mutations and common ones. It has been generally accepted that SNPs ...
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Single nucleotide polymorphisms (SNPs) are the most common form of genetic variant in humans, which can be generally classified into disease related mutations and common ones. It has been generally accepted that SNPs caused amino acid substitutions are of particular interest as candidates for affecting susceptibility to complex diseases, such as cancer, which is a serious public issue affecting millions of people worldwide each year. In this study, we have developed an automated and robust method to distinguish cancer-related mutations from common polymorphisms from amino acid sequence, which has a significant meaning for the cancer diagnosis, prognosis and treatment. Multiple different sequential features are extracted and the most important features are finally selected for constructing the prediction model. Experimental results show that an overall 81.07% success rate has been obtained, indicating the proposed method is very promising in the clinical cancer research studies.
We present an algebraic approach to multibody motion segmentation from line correspondences. Given three perspective views containing multiple linearly moving objects, we demonstrate that after applying a polynomial e...
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ISBN:
(纸本)0769523722
We present an algebraic approach to multibody motion segmentation from line correspondences. Given three perspective views containing multiple linearly moving objects, we demonstrate that after applying a polynomial embedding to the line correspondences, they became related by the so-called multibody line constraint of translational motions. We show how to linearly estimate the multibody trifocal epipole from line-line-line correspondences. The individual trifocal epipoles are then obtained from the derivatives of the multibody line constraint (up to an unknown factor). Given normalized trifocal epipoles, we can use any special clustering technique to obtain the clustering of the motions and the correspondences. The limitations of the proposed algorithm are also discussed. Experimental results on synthetic and real dynamic scenes are presented.
B-factor reflects the atom's uncertainty about its average position within a crystal structure and is highly correlated with protein functions. In this article, we propose a novel approach to predict the real valu...
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B-factor reflects the atom's uncertainty about its average position within a crystal structure and is highly correlated with protein functions. In this article, we propose a novel approach to predict the real value of B-factor. We firstly extract features from the protein sequences and their evolution information, then apply random forest tree to select the important features, which are further inputted to a two-stage support vector regression (SVR) for prediction. Our results have revealed that a systematic analysis of the importance of different features makes us have deep insights into the different contributions of features and is very necessary for developing effective B-factor prediction tools. We thus develop an online Web server, which is freely available at http://***/bioinf/PredBF for academic use.
By studying the MPEG-2 based output rate control strategy in detail, the mechanism of accurate bit-rate control and rational bit allocation is analyzed. To solve the difficulties of bit-rate control from the drastic c...
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ISBN:
(纸本)0780343719
By studying the MPEG-2 based output rate control strategy in detail, the mechanism of accurate bit-rate control and rational bit allocation is analyzed. To solve the difficulties of bit-rate control from the drastic changes of coded bits, a bit-rate control strategy under scene change is proposed.
In this article, we explain why and how to identify the projected sphere center, i.e. the projection of the sphere center, in passive-mode based optical tracking systems using infrared reflective spheres as markers. W...
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In this article, we explain why and how to identify the projected sphere center, i.e. the projection of the sphere center, in passive-mode based optical tracking systems using infrared reflective spheres as markers. We first present the algebraic representation of the 'deviation', defined by their Euclidian distance in the image coordinate system, between the projected sphere center and the center of the elliptical contour of the sphere's image, and show that the common approximation to substitute the later for the former is not always appropriate in terms of accuracy. Then, we give the projective equation of a sphere in matrix form, thus paving the way for the linear estimation of the projected sphere center. Sufficient experiments indicate that this proposed method enlarges the manipulating volume of the optical tracking system and improves the precision of locating surgical instruments.
Based on statistical learning theory, support vector machine (SVM) is a novel type of learning machine, and it contains polynomial, neural network and radial basis function (RBF) as special cases. The mapped least squ...
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Based on statistical learning theory, support vector machine (SVM) is a novel type of learning machine, and it contains polynomial, neural network and radial basis function (RBF) as special cases. The mapped least squares support vector machine (MLS-SVM) is a special least square SVM (LS-SVM), which extends the application of the SVM to the imageprocessing. Based on the MLS-SVM, a family of filters for the approximation of partial derivatives of the digital image surface is designed. Prior information (e.g., local dominant orientation) are incorporated in a two dimension weighted function. The weighted MLS-SVM with the radial basis function kernel is applied to design the proposed filters. Exemplary application of the proposed filters to fingerprint image segmentation is also presented.
This paper presents a novel facial localization method for 3D face in the presence of facial pose and expression variation. An idea of using Multi-level Partition of Unity (MPU) Implicits in a hierarchical way is prop...
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This paper presents a novel facial localization method for 3D face in the presence of facial pose and expression variation. An idea of using Multi-level Partition of Unity (MPU) Implicits in a hierarchical way is proposed for reconstruction of face surface. Based on the analysis of curvature features, nose and eyeholes regions can be detected on lower level reconstructed face surface uniquely. Experimental results show that this method is invariant to pose, holes, noise and expression. The overall performance of 99.18% is achieved.
Human facial shapes undergo significant variations from infancy to teenage, while they change limitedly as people age into adulthood. In this paper, facial shapes of males across ages using Euclidean distances are stu...
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Human facial shapes undergo significant variations from infancy to teenage, while they change limitedly as people age into adulthood. In this paper, facial shapes of males across ages using Euclidean distances are studied and a D-A standard (Distance related to Ages) is proposed for this purpose. Further, we determine the distance features that significantly contribute to the aging face recognition. Experimental results using the MORPH database containing age separated facial images are encouraging and illustrate Euclidean distance features improve the performance of face recognition across ages.
This paper is about a vision-based system that automatically monitors intermodal freight trains for the quality of how the loads (containers) are placed along the train. An accurate and robust algorithm to segment the...
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In this paper, we introduce methods to extract low-level features for soccer video analysis. A new method is proposed to segment players by using a mean distributed color feature. In order to discriminate which team t...
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ISBN:
(纸本)0780390059
In this paper, we introduce methods to extract low-level features for soccer video analysis. A new method is proposed to segment players by using a mean distributed color feature. In order to discriminate which team the player belongs to, we use mutual chromatic correlation degree of players to identify team without extracting templates of players in advance. Experimental results are included to show the effectiveness of the method.
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