TWSVM(Twin Support Vector Machines) is based on the idea of GEPSVM (Proximal SVM based on Generalized Eigenvalues), which determines two nonparallel planes by solving two related SVM-type problems, so that its computi...
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TWSVM(Twin Support Vector Machines) is based on the idea of GEPSVM (Proximal SVM based on Generalized Eigenvalues), which determines two nonparallel planes by solving two related SVM-type problems, so that its computing cost in the training phase is 1/4 of standard SVM. In addition to keeping the superior characteristics of GEPSVM, the classification performance of TWSVM significantly outperforms that of GEPSVM. In order to further improve the speed and accuracy of TWSVM, this paper proposes the twin support vector machines based on rough sets. Firstly, using the rough sets theory to reduce the attributes, and then using TWSVM to train and predict the new datasets. The final experimental results and data analysis show that the proposed algorithm has higher accuracy and better efficiency compared with the traditional twin support vector machines.
Linear Discriminant Analysis (LDA) is an efficient image feature extraction technique by supervised dimensionality reduction. In this paper, we extend LDA to Structured Sparse LDA (SSLDA), where the projecting vectors...
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Linear Discriminant Analysis (LDA) is an efficient image feature extraction technique by supervised dimensionality reduction. In this paper, we extend LDA to Structured Sparse LDA (SSLDA), where the projecting vectors are not only constrained to sparsity but also structured with a pre-specified set of shapes. While the sparse priors deal with small sample size problem, the proposed structure regularization can also encode higher-order information with better interpretability. We also propose a simple and efficient optimization algorithm to solve the proposed optimization problem. Experiments on face images show the benefits of the proposed structured sparse LDA on both classification accuracy and interpretability.
Rough set theory and fuzzy set theory are complementary generalizations of classical set *** paper concerns with rough sets,fuzzy sets and vector *** construct a rough fuzzy sets model based on a congruence of a vecto...
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Rough set theory and fuzzy set theory are complementary generalizations of classical set *** paper concerns with rough sets,fuzzy sets and vector *** construct a rough fuzzy sets model based on a congruence of a vector space and it is assumed that the knowledge about a vector space should be restricted by a ***, we research fuzzy subs paces of the vector space over a field, and get a series of properties. Specifically,we construct the minimum fuzzy subspace containing two fuzzy subspaces in a vector space. Secondly, we define concepts of the lower(upper) approximations of fuzzy subsets with respect to a subspace, and give some properties of the lower and the upper approximations of fuzzy subsets. Finally, we focus on fuzzy subspaces of the vector space, and define the lower(upper) rough fuzzy subspaces and the rough fuzzy subspaces of the vector space. We obtain that a fuzzy subspace is certainly a rough fuzzy subspace, the intersection and sum of two fuzzy subspaces are also rough fuzzy subs paces and other valuable results.
Analysis of the Vehicle Behavior is mainly to analyze and identify the vehicles' motion pattern, and describe it by the use of natural language. It is a considerable challenge to analyze and describe the vehicles&...
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Video-based Face Recognition (VFR) can be converted to the matching of two image sets containing face images captured from each video. For this purpose, we propose to bridge the two sets with a reference image set tha...
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Video-based Face Recognition (VFR) can be converted to the matching of two image sets containing face images captured from each video. For this purpose, we propose to bridge the two sets with a reference image set that is well-defined and pre-structured to a number of local models offline. In other words, given two image sets, as long as each of them is aligned to the reference set, they are mutually aligned and well structured. Therefore, the similarity between them can be computed by comparing only the corresponded local models rather than considering all the pairs. To align an image set with the reference set, we further formulate the problem as a quadratic programming. It integrates three constrains to guarantee robust alignment, including appearance matching cost term exploiting principal angles, geometric structure consistency using affine invariant reconstruction weights, smoothness constraint preserving local neighborhood relationship. Extensive experimental evaluations are performed on three databases: Honda, MoBo and YouTube. Compared with competing methods, our approach can consistently achieve better results.
We propose an approach to recognize group activities which involve several persons based on modeling the interactions between human bodies. Benefitted from the recent progress in pose estimation [1], we model the acti...
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We propose an approach to recognize group activities which involve several persons based on modeling the interactions between human bodies. Benefitted from the recent progress in pose estimation [1], we model the activities as the interactions between the parts belong to the same person (intra-person) and those between the parts of different persons (inter-person). Then a unified, discriminative model which integrates both types of interactions is developed. The experiments on the UT-Interaction Dataset [2] show the promising results and demonstrate the power of the interacting models.
Rough set theory and vague set theory are powerful tools for managing uncertain, incomplete and imprecise information. This paper extends the rough vague set model based on equivalence relations and the rough fuzzy se...
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Rough set theory and vague set theory are powerful tools for managing uncertain, incomplete and imprecise information. This paper extends the rough vague set model based on equivalence relations and the rough fuzzy set model based on fuzzy relations to vague sets. We mainly focus on the lower and upper approxima- tion operators of vague sets based on vague relations, and investigate the basic properties of approximation opera- tors on vague sets. Specially, we give some essential characterizations of the lower and upper approximation operators generated by reflexive, symmetric, and transi- tive vague relations. Finally, we structure a parameterized roughness measure of vague sets and similarity measure methods between two rough vague sets, and obtain some properties of the roughness measure and similarity measures. We also give some valuable counterexamples and point out some false properties of the roughness measure in the paper of Wang et al.
This paper present a geometric method to reconstruct human motion pose from 2D point correspondences obtained from uncalibrated monocular images. The proposed algorithm can handle images with very strong perspective e...
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Utility services provided by cloud computing rely on virtual customer communities forming spontaneously and evolving continuously. Clarifying the explicit boundaries of these communities is thus essential to the quali...
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In delay tolerant networks (DTNs), message delivery is operated in an opportunistic way through store-carry and forward relaying, and every DTN node is in anticipation of cooperation for data forwarding from others. U...
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In delay tolerant networks (DTNs), message delivery is operated in an opportunistic way through store-carry and forward relaying, and every DTN node is in anticipation of cooperation for data forwarding from others. Unfortunately, there always exist some selfish nodes that are reluctant to contribute to this cooperative data forwarding procedure so as to save their valuable storage buffer, limited computation power and precious energy. In order to stimulate nodes' willingness to participate in data forwarding, a number of incentive schemes have been proposed recently. However, most existing incentive schemes simply ignore efforts of nodes involved in message delivery if messages delivered fail to reach their destinations. Due to the nature of DTN, such as intermittent connectivity, it is not unusual to have unreliable message delivery, which results in unrewarded or wasted efforts for participating nodes and may discourage them from participating in future data forwarding. Therefore, it is crucial to recognize contribution of every node involved in a data forwarding procedure even the message it helps to forward doesn't successfully reach its destination. However, how to track all delivery paths so as to give every intermediate node some incentive for their cooperative efforts of data forwarding is still an open research problem. To address this problem, we propose a secure message forwarding scheme with path tracking. The proposed method is end-to-end secure with data source and identity authentication. In addition, it can thwart some well known attacks including edge inserting attack, sibling inserting attack and free riding attack.
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